EDA_1.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "0fcc2ec8",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import scipy.stats as stat\n",
    "import statsmodels.api as smf\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "5cd7da91",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sepal_length</th>\n",
       "      <th>sepal_width</th>\n",
       "      <th>petal_length</th>\n",
       "      <th>petal_width</th>\n",
       "      <th>species</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>6.7</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>2.3</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>6.3</td>\n",
       "      <td>2.5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.9</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>6.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>6.2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>5.4</td>\n",
       "      <td>2.3</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>5.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.1</td>\n",
       "      <td>1.8</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>150 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     sepal_length  sepal_width  petal_length  petal_width    species\n",
       "0             5.1          3.5           1.4          0.2     setosa\n",
       "1             4.9          3.0           1.4          0.2     setosa\n",
       "2             4.7          3.2           1.3          0.2     setosa\n",
       "3             4.6          3.1           1.5          0.2     setosa\n",
       "4             5.0          3.6           1.4          0.2     setosa\n",
       "..            ...          ...           ...          ...        ...\n",
       "145           6.7          3.0           5.2          2.3  virginica\n",
       "146           6.3          2.5           5.0          1.9  virginica\n",
       "147           6.5          3.0           5.2          2.0  virginica\n",
       "148           6.2          3.4           5.4          2.3  virginica\n",
       "149           5.9          3.0           5.1          1.8  virginica\n",
       "\n",
       "[150 rows x 5 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('https://github.com/raw/uiuc-cse/data-fa14/gh-pages/data/iris.csv')\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca4120c4",
   "metadata": {},
   "source": [
    "# Univariate Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "d1454fee",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_setosa=df.loc[df['species']=='setosa']\n",
    "df_virginica=df.loc[df['species']=='virginica']\n",
    "df_versicolor=df.loc[df['species']=='versicolor']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "b6f74374",
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (10,6))\n",
    "plt.plot(df_setosa['sepal_length'], np.zeros_like(df_setosa['sepal_length']), 'x')\n",
    "plt.plot(df_virginica['sepal_length'], np.zeros_like(df_virginica['sepal_length']), 'x')\n",
    "plt.plot(df_versicolor['sepal_length'], np.zeros_like(df_versicolor['sepal_length']), 'x')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3bd6d1e6",
   "metadata": {},
   "source": [
    "# Bivariate Analysis\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "13b3e8ec",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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zpGckfbj0BTMbRaMPlKbCbdu1V4tWbpKkspt0GnMAmStNrNv9RPBcKkyjX7J2iW7afNPB5wf8wMHn5Tb60oS77Xu2q+PeDkmi0aNqyvlMfr2kdeH3nZIek/Sr8PH67EqrL2mkwpEsh7pQoMS6OMsfW55oPAoJd6gFgzZ5d3+Zux8jaY2ks9x9tLv/paR5klZmXWC9SCMVjmQ51IUCJdbFOeAHEo1HIeEOtSDJ6vpXu/vtPU/c/fuSXpt+SfUpjVQ4kuVQFwqUWBenyaL/0xg3HoWEO9SCJE3+aTNbbGaTzOxoM/tXSb/LqrB6k0YqHMlyqAsFSqyLs+D4BYnGo5Bwh1pQzsK7HudJukjSLeHzn4Zj0AsL4ypZGZ/GHEDmehbXFXh1fc/iukpW1/csrmN1fTGZ2e2S3uHuu/KuZSBlp9DVElLoAKCukUJXJYOerjezL4bfbzWz75V+ZV4hAABDYGbDzWy1mT1oZg+Z2UIze9zMvmBmvwi/Xh5uO8bMbjaz+8OvWeH4i83sm2a2ycw2mtnbwvHHzWx0+Phd4VwPmNnXzKw5/Lo23O8mM/t4Hr+Dck7X/2f4naAaAEA9OVPSk+4+V5LMbISkL0h6xt1PNrN3S/qigqvFOiVd5u53m9lRCq4o+ytJn5a0292nhHP8Re8dmNlfSVooaZa77zezr0h6p6SHJY139xPC7UZmfbBRygmo6bkWvlnSWnf/Y7YlAQCQik2S/iMMU7vN3X9mZpJ0Y/j6jZIuCx+/XtIrw9cl6SVmdng4/vaeQXf/Q8k+Tpc0Q9L94c+2SnpK0q0Kbgd/haTVku5I99DKk2Th3fmSrjSz30n6Wfh1d8QBAwCQO3d/zMxmSHqTpEvMrKfR9l6M1vO4SdKp7t7nxiQWdO6BFq+ZpOvcfVG/F8xOlHSGgjvGnivp74d0IBUo+xI6d3+3ux8v6W2Stkr6soK73gEAUHPM7EhJf3T3byv4yHl6+NLCXt9/Hj6+Q9JHev3sSTHjfU7XS7pL0jlmdkT4+qjwMvPRkprc/WYFp/ynKwdlv5M3s3dJ+mtJUyQ9LelLCt7NAwBQi6ZIWmpmByTtl/RBSSskvcjM7lPwRrfnUvCPSvpymLZ6iILLxD8gaUk4/pCkbkmfVa+7vbr7L81ssaQ7zKwp3M+HJe2V9M1wTJL6vdOvhrIvoTOzpyX9WtKVkn7k7o9nWNeAqnUJXVwi3OJVm3TjfU+o213NZjrvlIlaMn9KogQ50uZQc5Iky8Vtm0I6XZLktixT3tKogxS6WLldQmdmj0tqc/en86qhmhJdJ29mr5L0N5JeI+k4SZvd/e8yqi1WNZp8aSKcFNx9bvpRI3TPr/sH7806dpS6fru73/aXnD2lX/OOmztqW6AqSpPlpOAudmdd3r9Jx2174jukB28ob44YpcltUnCXuI7TOvo1xyTbJpVGHW95+Vv03f/+bib1FQBNvkqSvJN/iaRZCu5X/9eSRitYbf+e7MqLVo0mP+vzP9S2FIJhxo9s1T2ffF1Zc0dtC1TFZScEkbGlRkyUPv5Qedtas+Td/cej5ogxZ8Ucbd+zvd/4uOHjdMc5dwx526TSqKPJmiIDbdKorwC4GU6VJFldf3evry+5e3EipyKklfwWNQ9pc6g5SZLl4raNavADbR8hSXJblilvadQRl1hHCh2qKcnq+qnu/iF3vyGqwYfXAhZGWslvUfOQNoeakyRZLm5ba44eT5BOlyS5LcuUtzTqiEusI4UO1ZQkhW4ws1KcK3dxiXCzjh0Vuf2sY0eVnSBH2hxqTpJkubhtZ5xfcTpdkuS2LFPe0qhjwfELSKFD7pKcrm8oAyXCVbq6nrQ51JwkyXIDbXvUzIpW1ydJbssy5S2tOqYdMY3V9chVail0Ztbl7lW52J8UOgCoa3W58M7Mzpd0h7s/mXct5UrznXxd/qMBAOrDpE+ufoekf5d0lKTfSvrU45+fe0MVSzhf0kOS6qbJp/mZfGeKcwEAcFDY4K+WdLSCN5VHS7o6HB+ymDjaGWb2EzNbb2ZrzGycmZ0jqU3S9WGkbKuZnW5mG8Io2W+Y2YvCOT9vZr8Mo2n/Ixw7y8zuC7f/LzN7aUW/kDIN+k7ezG7VADfnd/c3h9+vTa8sAAD6+HdJh5WMHRaOV/JuPiqO9vuS3uLuO81soaR/c/e/N7OPSPpnd19nZsMkXSvp9DAI51uSPhh+f6ukV7i794qYvVvSzHDs/0j6hKR/qqDuspRzup4ceQBA3o5KOF6uPnG0kv4g6QRJd4bRsc2S+t/tSJos6Tfu/lj4/DoF96z/kqR9kr5uZqvDOSVpgqSbzGycpEMl/abCustSTp78T6pRCAAAA/itglP0UeNDVhpHK+lOSQ+7+6mD/GjkOjR3f97MTlaQM/92BQl2r5N0haRL3f17ZjZbUkcldZer7M/kzew4M1sRfs6wpecry+IAAAh9StIfS8b+GI4PWUQc7SmSxpjZqeHrLWFuiyQ9K+nw8PGjkiaZ2cvD538n6Sdm9mJJI9z9dkkfk3RS+PoISdvCx1W7HXyS1fXflHSRpMsk/a2k94oV9YN6w6U/1q+e2nPw+XFHDNedF8wmhQ75SSEpLpXEuhhpJLdFzSFFX8tOUlx9ePzzc2+Y9MnVUvqr66PiaJ+XdHn4+fwhkr4o6WEFn8FfaWZ7JZ2qoA8uN7NDJN2vIKV1lKTvhp/Zm6SPh/vpCLfdJmmtpJdVWHdZkgTUrHf3GWa2yd2nhGM/c/e/zrTCCPVynXxpg+/x0sMP1TP7ukmhQ/UlSZtLY46E+0sjWS5qjpamFrm7nvfn+8xLUlxueINYJUkuodtnZk2SfmVmHzGzt0o6IqO6CiGqwUvS/z775z4NXpL27u/W0jWbq1EWGtldF/dtuFLw/K6Ls5kj4f46uzr7NFxJ2te9T51d5V+hGzXH/gP7+zT4nnmXP7a84v0BtSxJk/+YgssVPipphoLPH6oeM1tkpNAhc0nS5tKYI+H+0kiWS7ItSXEouiQpdPe7+3OSnpH0UXc/293XZlda4yGFDplLkjaXxhwJ95dGslySbUmKQ9ElWV3fZmabJG2UtCm8O9CM7Eqrf8cdMTxy/KWHH0oKHfKRJG0ujTkS7i+NZLmoOVqaWnSI9V1nTFIcGkGS0/XfkPQhd5/k7pMUXPT/zUyqKog7L5jdr9Efd8Rw3fevb9AlZ0/R+JGtMknjR7ay6A7VMfXcYNHbiImSLPieZNFd0jkS7m/uMXPVcVqHxg0fJ5Np3PBxiRfBRc3xuVmf05LXLOk37+KZiyveH1DLkqyuv8fdZw02Vg31sroeABCJ1fVVkuSd/C/M7GtmNtvMXmtmX5H0YzObbmZViZgFAKCWmdnFZvb6IfzcbDO7bfAtk0lyM5yTwu8XlYyfpiDA5nVpFAQAQKSOEf2iZtWxu5pRs5IkC25qb+79L89w9wQLXCqq4RD3kutCI5Td5N39bysrCQCAIQoa/NV6IYnuaElXq2OEhtrow1Ca/3H3r4TPOxTcurZJ0rmSXiTpFne/yMwmKUin+5GCu93NN7PPKoifdUnfcPfLzOxaSbe5+woze7WCGPbhkv6k4H72+yV9Nfy55yVd4O4/KqlrlIJ1cMcouHXv+919Y1jfkZImSXpa0qAxu0lW17/UzK4xs++Hz19pZv9Q7s8DAFCBgaJmh+o7khb2en6upJ2SjpN0soIz2DPM7G/C1ydL+pa7T5M0WtJ4dz8hvAtsn4XoZnaopJsktbv7iZJeL2mvgkXrCn/mPEnXhbfA7e2zkja4+1QF9+b/Vq/XZiiIwR20wUvJPpO/VtIaBX9FSNJjCm6QAwBA1lKPmnX3DZKOMLMjzexEBTGzUyXNkbRBUpekVyho+lLwrr/n/jBbJB1jZleY2ZkK7iHT22RJ2939/nBfz4Sn118j6T/DsUcl/Y+k40t+tvc2P5T0l+F99CXpe+5e9p3TkjT50e6+TNKBcMfPS+oe+EcAAEhFXKRsRVGzklZIOkfBO/rvKFj5f4m7nxR+vdzdrwm3PXivcnf/g6QTJf1Ywbvzr5fMawpO45cq58qCqG165oq+X3qMJE1+j5n9Zc+OzGympN1JdgYAwBBlEjWroLG/XUGjX6HgjPXfh5GxMrPxZtYvp8XMRktqcvebJX1aUulVZo9KOjL8XF5mdniYVvdTSe8Mx45XcCaiNLik9zazJT3t7qVnCsqSZHX9BZK+J+lYM7tH0hgFv5RY4ecMP1WweOEQSSvc/aKSbUzBwoQ3KfgHO9/duxLUlYok0a9x277z6p/rnl///uB2s44dpevfd2rF+wMOiottve0Caf21kndL1izNOF+ad2nlcxw1s+KYWCk64jWujqg5Njy1QcsfW64DfkBN1qQFxy/Q4pmLE/3qlqxdktkcSeJq84i2LUScbsfuG9QxQkp5db27P2xmh0va5u7bJW03s7+S9POgPek5Se9S/zPX4yV9Mwxuk6RFJfP+2cwWSrrCzFoVfB7/eklfURBXu0nBwrvz3f1P4b4OHm0490YFfXHIOTFJboazQMFfOBMlvU3SKZI+PVBDDhv4cHd/zsxaJN2tYBHC2l7bvEnSPypo8qdI6nT3UwaqJe2b4azasE2LVm4qK/o1btsJfzEsMnUuqtEn2R9wUFxs64STpd/8pP/2bf/Qv9EnnaOpWTrQ3XfbBDGxcRGvHRPO1Nx7ru5Xx+pZ71PH1h/0maPZmtXt/T8ZXDh5YdlNesnaJbpp802ZzDFz7Ew9sPOBsuJq04jSTSqPfZaBm+FUSZLT9Z8OTxf8hYK/Rq5ScBlALA88Fz5tCb9K/6p4i4LVih42/5FmNi5BXRVbumZz2dGvcdvGxcr2fmc/lP0BB8XFtkY1Zyl4V17pHAe6+2+bICY2LuK1c8stkXV0brml3xxRDV6Slj+2PLrmBNumMcfaHWvLjqtNI0o3qTz2idqRpMn3/D9trqQr3f27kg4d7IfMrNnMHpD0lKQ73f2+kk3GS3qi1/Ot4VjpPO83s3Vmtm7nzp0Jyh5cXMRr1HgacbBJ9gcclCQOVgpOu1c6R4I6EsXBxvyXJ248SlxMbJJt05gjTtTvI40o3aTy2CdqR5Imv83MvqbgOsLbzexF5fy8u3e7+0mSJkg62cxOKNlkoFWEvee5yt3b3L1tzJgxCcoeXFzEa9R4GnGwSfYHHJQkDlYKPlevdI4EdSSKg43pl3HjUeJiYpNsm8YccaJ+H2lE6SaVxz5RO5L8r/ZcBZ/Jn+nuuySNknRhuT8c/syPJZ1Z8tJWBZ/z95gg6ckEdVXswjMmlx39GrdtXKzsrGNHVbQ/4KC42NaXvTZ6+xnnVz5HU3P/bRPExMZFvLYf89bIOtqPeWu/OZqj/liRtOD4BdE1J9g2jTlmjp1ZdlxtGlG6SeWxT9SOspu8u//R3Ve6+6/C59vd/Y6BfsbMxpjZyPBxq4LP8h8t2ex7kt5tgZmSdocrHKtm/rTxZUe/xm175wWz+zX0uNX1SfYHHBQX2/qe7wWL7HqaoTVHL7obyhzzr6woJjYu4nXu7M9F1jF39uf6zfFvr/k3LZy88OA76SZrSrRgTpIWz1yc2RxXn3F12XG1aUTpJpXHPlE7yl5dP6TJzaZKuk5Ss4I/KJa5+8Vm9gFJcvcrwxX4X1LwDv+Pkt7r7gMunSdqFgDqGqvrqyTJdfKJuftGSdMixq/s9dgV3ssXAIA8mdmRki539wHvAxPxc7dLekf40XTcNhdL+qm7/1dlVSaoK8t38lnhnTwA1LUhvZOfct2UflGzm96zqSpRs+VGu9aaZMtFAQDIQdjgr1YQMWvh96vD8SExsy+Y2Yd6Pe8ws38ys4fC5+eb2XIzu1XSHWZ2mJktM7ONZnaTmd1nZm3hto+b2Wgzm2Rmj5jZ1Wb2sJndEa5Jk5lda2bnhI9fbWb3mtmDZvaL8La3k8zsZ2bWFX6dNtRj60GTBwDUg2pFzd5fss2pkt7j7q+T9CFJfwgjYD+nIPY1ynGSvuzur5K0S8FdYg8aIIb2KUlvcPfpYV2XD/3QApl+Jg8AQEoyiZo1syPCz+HHKIiaLU21u9Pde25d+hoFWSty94fCe8tH+Y27PxA+Xi9pUsnr/WJoJcnMhkv6kpmdpOAGdKURtInR5AEA9eC3Ck7RR41XoidqdqyCd/alet+zvNy1BH/q9bhbUumdzuJiaD8u6X8VRNg2SdoXsU0iNPkUkSzXgOIS3Wqhjt+uLT+ZLm4OKfr4auW4U1DrCW21Xl8VfUrBZ/K9T9mnFTV7taTRkl6rIDU1zt0KTun/yMxeKWnKEPd5MIbW3e8PU/D2Shohaau7HzCz9yi4/LwiNPmUlCbLbdu1V4tWbpIkGn1RlSa67X4ieC5Vt+FF1XHLB/reu967pXXXBI+jGn3UHN/9sOQuHdj/wtitHw3+eHjwhvyPOwWlCW3b92xXx70dklQTjbTW66umTe/ZdMOU66ZIKa+uL42aNbNJA2z+FUnXhafpN0jaKGn3EPY5UAztzWHq64/U9yzCkHAJXUpmff6H2hYRMDN+ZKvu+eTrcqgImbvshKDBlRoxUfr4Q/nXEcWapYv6JyMmniMq/Kbax52COSvmaPue/jfYHDd8nO44Z8AbelZFrddXgbq8GY6ZNUtqcfd9ZnaspLskHe/uf865tFi8k08JyXINKC7RLY2ktzTqiBIT21r1OWpErSe01Xp9DegwBafqWxT8ofLBWm7wEpfQpYZkuQYUl+iWRtJbGnVEiQl7qfocNaLWE9pqvb5G4+7PhmmoJ7r7VHf/ft41DYYmnxKS5RpQXKJbTEpbVeuIa8RRyXRxczQfKjW19B1raQ3mqIXjTkGtJ7TVen2ofZyuT0nP4jpW1zeQnkVmea8yj6sjyer6uDmixqaeKx01M//jTkHP4rVaXb1e6/Wh9rHwDgBQbXW58K4ecboeAICCoskDAFBQNHkAAAqKJg8AQEHR5AEAKCiaPAAABcV18kAtikt5yzL9LYUUutU//rQ6t9yiHU3S2ANS+zFvlY6ameg67yVrl2j5Y8t1wA+oyZq04PgFWjxzcTrHWAP7q6VUuVqqBdngOnmg1pQmwknBHeVOfEff9Lee8bMur7zRR+2z+dC+KXSD1LF68t+q49lN2tf0wiXQLe5ya9bzOnBwbFjzMHWc1hHZTJasXaKbNt/Ub3zh5IWZNN5q7680VU4a+PeRpZxr4Tr5KqHJA7UmLhEuy/S3FFLo5kw8UtsPKe/kYFyK2onfOlEH/EC/8SZr0oPvfrC8+hKo9v5qKVUu51po8lXCZ/JArYlLc8sy/S2FFLodzTH3y4/aNiZFLarhDjReqWrvr5ZS5WqpFmSHJg/Umrg0tyzT31JIoRvbHfNHSNS2MSlqTRb9n6S48UpVe3+1lCpXS7UgOzR5oNbEpdtlmf6WQgpd+4iTNOxA34//Wtx1SMl/ZgZKUVtw/IJE45Wq9v5qKVWulmpBdmjyQK2Zem6wmG7EREkWfD/r8iBBLmo8jdX1Uft8y5el+V8pu46559yojpe9VeO6Xeaucd2uz016q5b89b9r3PBxMpnGDR834MKuxTMXa+HkhQffSTdZU2aL4PLY39xj5qrjtI6yfx9ZqqVakB0W3gEAqo2Fd1XCO3kAAAqKJg8AQEHR5AEAKCiaPAAABUWTBwCgoGjyAAAUFE0eAICCImoWyNttF0jrrw3uCW/NwR3l5l0avW0eEbQVShpnuuS287X86XU6oOBdyILRbVo879pU5gYaDTfDAfJ02wXSumv6j7f9Q/9Gn0cEbYWSxpkuue183fT0Osl63SvFXQsjGn0txbYiMW6GUyWcrgfytP7a8sfvurhvI5eC5+uvjR6/6+IUCqxMZ1dnnyYsSfu696mzqzNy++WlDV6SzILxCucGGhFNHshTXHxs1HgeEbQVShpnGhfwGjVOVCowOJo8kKe4+Nio8TwiaCuUNM407j9IUeNEpQKDo8kDeZpxfvnjeUTQVihpnOmC0W1S6Toh92C8wrmBRkSTB/I079JgkV3Pu3Frjl50J+UTQVuhpHGmi+ddq4Wj29TkLrmrKWbR3VDmBhoRq+sBANXG6voq4Z08AAAFRZMHAKCgaPIAABQUTR4AgIKiyQMAUFA0eQAACoomD5Rj4zLpshOkjpHB943L6nd/1T6WGrd6y2rNWTFHU6+bqjkr5mj1ltV5l1ST+D3VJ6JmgcGUpr/tfiJ4LmVzw5ks91ftY6lxpUl22/dsV8e9HZLETXV64fdUv3gnDwwmLv0tq5S3LPdX7WOpcSTZlYffU/2iyQODiUtzyyrlLcv9VftYahxJduXh91S/aPLAYOLS3LJKectyf9U+lhpHkl15+D3VL5o8MJi49LesUt6y3F+1j6XGkWRXHn5P9YuFd8Bgehak3XVxcFp7xISgKWa1UC3L/VX7WGpcz6Kxzq5O7dizQ2OHj1X79HYWk5Xg91S/SKEDAFQbKXRVwul6AAAKiiYPAEBB0eQBACgomjwAAAVFkwcAoKBo8gAAFFSm18mb2URJ35I0VtIBSVe5e2fJNrMlfVfSb8Khle7emDfSRnk2LivWdd5RxyNV/RhXb1mdzXXQMf9eS9Yu0fLHluuAH1CTNWnB8Qu0eObiyveXocx+R0BGMr1O3szGSRrn7l1mdrik9ZLmu/sve20zW9I/u/u8cuflOvkGVpqiJgV3bDvr8vps9FHH09QimUndf35hLONjLE0Zk4I7mnWc1lFZE4v591py4pm66Xfr+22+cPLCmm30mf2OGhPXyVdJpqfr3X27u3eFj5+V9Iik8VnuEwVXtBS1qOM5sL9vg5cyP8bMUsZi/r2WPx39R/ryx5ZXtr8MkcSGelS1z+TNbJKkaZLui3j5VDN70My+b2avivn595vZOjNbt3PnzixLRS0rWopakrozPMbMUsZiaj4Qs/kBj3slfySxoR5Vpcmb2Ysl3SzpY+7+TMnLXZKOdvcTJV0haVXUHO5+lbu3uXvbmDFjMq0XNaxoKWpJ6s7wGDNLGYupOe4/PE1Wu2uBSWJDPcr8/1Fm1qKgwV/v7itLX3f3Z9z9ufDx7ZJazGx01nWhThUtRS3qeJpapOZD+45lfIyZpYzF/HstGN0WufmC4xdUtr8MkcSGepRpkzczk3SNpEfc/dKYbcaG28nMTg5r+l2WdaGOTT03WIA2YqIkC77X66I7Kfp45n9FesuXq3qMc4+Zq47TOjRu+DiZTOOGj0tnQVnMv9fieddq4eSFB9+5N1lTTS+6kzL8HQEZynp1/Wsk/UzSJr3wMdynJB0lSe5+pZl9RNIHJT0vaa+kC9z93oHmZXU9ANQ1VtdXSabXybv73RrkH9PdvyTpS1nWAQBAI6rdVS4AAKAiNHkAAAqKJg8AQEHR5AEAKCiaPAAABUWTBwCgoGjyaEwbl0mXnSB1jAy+b1yW/dxZ7hMAImR6nTxQk0rjT3c/ETyXKr+rXNzcv10rPXhDNvsEgBi8k0fjyTKuNm7u9dcWKyIXQF2gyaPxZBlXGzeHd2e3TwCIQZNH48kyrjZuDmvObp8AEIMmj8aTZVxt3Nwzzi9WRC6AukCTR+PJMq42bu55lxYrIhdAXcg0ajYrRM0CQF0jarZKeCcPAEBB0eQBACgomjwAAAVFkwcAoKBo8gAAFBRNHgCAgiKgZghWbdimpWs268lde3XkyFZdeMZkzZ82Pu+ykMTGZcF943dvDe46d/pnauua9Szrq/VjB5AamnxCqzZs06KVm7R3f3Av8m279mrRyk2SRKOvF1mm0KUhj5S8NOYGUHM4XZ/Q0jWbDzb4Hnv3d2vpms05VYTEskyhS0MeKXm1cuwAUkWTT+jJXXsTjaMGZZlCl4Y8UvJq5dgBpIomn9CRI1sTjaMGZZlCl4Y8UvJq5dgBpIomn9CFZ0xWa0vf2NDWlmZdeMbknCpCYlmm0KUhj5S8Wjl2AKli4V1CPYvrWF1fx3oWmNXqCvMs66v1YweQKlLoAADVRgpdlXC6HgCAgqLJAwBQUDR5AAAKiiYPAEBB0eQBACgomjwAAAVFkwdq0cZl0mUnSB0jg+8blxVun6u3rNacFXM09bqpmrNijlZvWZ3p/oBGxM1wgFqTR1Jclfe5estqddzboX3d+yRJ2/dsV8e9HZKkucfMTX1/QKPinTxQa/JIiqvyPju7Og82+B77uveps6szk/0BjYomD9SaPJLiqrzPHXt2JBoHMDQ0eaDW5JEUV+V9jh0+NtE4gKGhyQO1Jo+kuCrvs316u4Y1D+szNqx5mNqnt2eyP6BRsfAOqDV5JMVVeZ89i+s6uzq1Y88OjR0+Vu3T21l0B6SMFDoAQLWRQlclnK4HAKCgaPIAABQUTR4AgIKiyQMAUFA0eQAACoomDwBAQdHkAQAoKJo8AAAFRZMHAKCgaPIAABQUTR4AgIKiyQMAUFA0eQAACoomDwBAQdHkAQAoKJo8AAAFRZMHAKCgaPIAABQUTR4AgIKiyQMAUFA0eQAACirTJm9mE83sR2b2iJk9bGbtEduYmV1uZv9tZhvNbHqWNQFDsnGZdNkJUsfI4PvGZXlXBACDOiTj+Z+X9E/u3mVmh0tab2Z3uvsve23zRknHhV+nSPpq+B2oDRuXSbd+VNq/N3i++4nguSRNPTe/ugBgEJm+k3f37e7eFT5+VtIjksaXbPYWSd/ywFpJI81sXJZ1AYncdfELDb7H/r3BOADUsKp9Jm9mkyRNk3RfyUvjJT3R6/lW9f9DQGb2fjNbZ2brdu7cmVmdQD+7tyYbB4AaUZUmb2YvlnSzpI+5+zOlL0f8iPcbcL/K3dvcvW3MmDFZlAlEGzEh2TgA1IjMm7yZtSho8Ne7+8qITbZKmtjr+QRJT2ZdF1C20z8jtbT2HWtpDcYBoIZlvbreJF0j6RF3vzRms+9Jene4yn6mpN3uvj3LuoBEpp4rnXW5NGKiJAu+n3U5i+4A1LysV9fPkvR3kjaZ2QPh2KckHSVJ7n6lpNslvUnSf0v6o6T3ZlwTkNzUc2nqAOpOpk3e3e9W9GfuvbdxSR/Osg4AABoRd7wDAKCgaPIAABQUTR4AgIKiyQMAUFA0eQAACoomDwBAQdHkAQAoKJo8AAAFRZMHAKCgaPIAABQUTR4AgIKy4Nbx9cXMdkr6nwqnGS3p6RTKqWVFP8aiH5/EMRYFx9jX0+5+ZpbFIFCXTT4NZrbO3dvyriNLRT/Goh+fxDEWBceIvHC6HgCAgqLJAwBQUI3c5K/Ku4AqKPoxFv34JI6xKDhG5KJhP5MHAKDoGvmdPAAAhUaTBwCgoBquyZvZN8zsKTN7KO9asmBmE83sR2b2iJk9bGbtedeUNjMbZma/MLMHw2P8bN41ZcHMms1sg5ndlnctWTGzx81sk5k9YGbr8q4nbWY20sxWmNmj4f8nT827pjSZ2eTw367n6xkz+1jedeEFDfeZvJn9jaTnJH3L3U/Iu560mdk4SePcvcvMDpe0XtJ8d/9lzqWlxsxM0nB3f87MWiTdLand3dfmXFqqzOwCSW2SXuLu8/KuJwtm9rikNncv5I1izOw6ST9z96+b2aGSDnP3XTmXlQkza5a0TdIp7l7pzcqQkoZ7J+/uP5X0+7zryIq7b3f3rvDxs5IekTQ+36rS5YHnwqct4Veh/lo1swmS5kr6et61YGjM7CWS/kbSNZLk7n8uaoMPnS7p1zT42tJwTb6RmNkkSdMk3ZdzKakLT2U/IOkpSXe6e9GO8YuSPiHpQM51ZM0l3WFm683s/XkXk7JjJO2U9M3wY5evm9nwvIvK0Nsl3Zh3EeiLJl9QZvZiSTdL+pi7P5N3PWlz9253P0nSBEknm1lhPnoxs3mSnnL39XnXUgWz3H26pDdK+nD4cVpRHCJpuqSvuvs0SXskfTLfkrIRfhTxZknL864FfdHkCyj8nPpmSde7+8q868lSePrzx5KKFHYxS9Kbw8+rvyPpdWb27XxLyoa7Pxl+f0rSLZJOzreiVG2VtLXXWaYVCpp+Eb1RUpe7/2/ehaAvmnzBhIvSrpH0iLtfmnc9WTCzMWY2MnzcKun1kh7NtagUufsid5/g7pMUnAL9obu/K+eyUmdmw8PFoQpPY8+RVJirXtx9h6QnzGxyOHS6pMIsgC1xnjhVX5MOybuAajOzGyXNljTazLZKusjdr8m3qlTNkvR3kjaFn1lL0qfc/fb8SkrdOEnXhat5myQtc/fCXmZWYC+VdEvwd6kOkXSDu/8g35JS94+Srg9PZ2+R9N6c60mdmR0m6Q2S/m/etaC/hruEDgCARsHpegAACoomDwBAQdHkAQAoKJo8AAAFRZMHAKCgaPIAABQUTR5IiZmdb2ZHlrHdtWZ2zgCv/9jM2lKubaSZfajX89lFjrAFEKDJA+k5X9KgTT4nIyV9aLCNABQLTR6IYWaTzOxRM7vOzDaa2QozO8zMZpjZT8LktDVmNi58Z96m4O5mD5hZq5l9xszuN7OHzOyq8JbDSWuYY2Y/N7MuM1seBg/JzB43s8+G45vM7BXh+BgzuzMc/5qZ/Y+ZjZb0eUnHhrUtDad/cXhMj5rZ9UOpD0Bto8kDA5ss6Sp3nyrpGUkflnSFpHPcfYakb0j6N3dfIWmdpHe6+0nuvlfSl9z91e5+gqRWSfOS7DhszoslvT5Malsn6YJemzwdjn9V0j+HYxcpuNf9dAWBL0eF459UkPV9krtfGI5Nk/QxSa9UEIs6K0l9AGpfw927HkjoCXe/J3z8bUmfknSCpDvDN77NkrbH/OzfmtknJB0maZSkhyXdmmDfMxU04HvCfR0q6ee9Xu9JGFwv6ezw8WskvVWS3P0HZvaHAeb/hbtvlaQw52CSpLsT1AegxtHkgYGVhjs8K+lhdz91oB8ys2GSviKpzd2fMLMOScMS7tsk3enu58W8/qfwe7de+P9yklPuf+r1uPccAAqC0/XAwI4ys56Gfp6ktZLG9IyZWYuZvSp8/VlJh4ePexr60+Hn6LGr6QewVtIsM3t5uK/DzOz4QX7mbknnhtvPkfQXEbUBaBA0eWBgj0h6j5ltVHDK/QoFDfsLZvagpAcknRZue62kK8NT33+SdLWkTZJWSbo/6Y7dfaeCFfs3hvtfK+kVg/zYZyXNMbMuSW9U8FHCs+7+OwWn/R/qtfAOQMERNQvEMLNJkm4LF87VBTN7kaRud38+PNvwVXc/KeeyAOSEz+CAYjlK0jIza5L0Z0nvy7keADninTyQEzO7RdLLSob/xd3X5FEPgOKhyQMAUFAsvAMAoKBo8gAAFBRNHgCAgqLJAwBQUP8figJZ/RX01nMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 516.75x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.FacetGrid(df, hue = 'species', size = 6).map(plt.scatter,\"petal_length\",'sepal_width').add_legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b72bd922",
   "metadata": {},
   "source": [
    "# Multivariate Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "ac2cc8a1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x1c76762dbe0>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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e3vc2lY2VXJ18NdsKt/FN5jcAfH34a+4eeze3jLzFyVgRCAQnjyRJXBJ/CZ5unixJX0KEKYJL4i/hobUPUd5YDsD7B97n/XPeJ9EnsZ97KxjIHCg/wA3Lbmjf2V6SvoS35r/Fc7Oe4/397+OucefGkTcy0m9kP/dUcDogjBAXkFdpwc/j+ApBPh46iqpFXIhg8KJRaZgYPJExAWOw2W1sK+4wQNp4Y88bnBt9LmGmsH7qpUAwNPEz+LEgcQHnx5yP1W7lpp9vajdAABqsDewo2SGMEMFx2VCwwcm19uWdL7N4/mJmh81GJamE4qGgzxDLlS4gp/zEOyFeBh0Fwh1LMATQqXUYtIYu/dGtdit22d4PvRIITg+MWiMSEk22JqdzIkZEcCLaxkiYKYx4r3gkJBptjdhlO3qNXhgggj5F7IS4gNzKBqbH+R23jo+7jgKxEyIYQsR5xeHp5kl1U3V72eNTH2dDwQZe2P4Ck4MnMyN0hsOuiKXFwq7SXXyX+R1mrZlzY85lpN9IJEnq9n3LLeVsKdrC8uzlJPkmcUbEGSJfgmDIUNZQxsbCjazKWcVw3+FMD51Obm0uP2X/RLgpnBjPGArqCngg5QEeWPMADVZFnU6j0jA+YHw/917Qn+TV5rE2fy2bCjcxNXgq08OmE+oR6lBnRugM3LXupFek02Bt4ILYC4j2jMaoNfZpX2uaathWvI2fspRxPT9qPkk+SX3aB0H/I4wQF5BXaSHApD9uHR+jjozi2j7qkUDQ+0R6RvLm/Df5LP0zDpQf4KYRN/H1oa9Zm69IO67KWcWk4Em8MOsFPN08AdhSvIW7Vt7V3sZnGZ/x/jnvM8JvRLfuaZftLElfwqu7XwVgec5yPk//nHfPedfpZSsQDDZa7C18kPoBb+97G4AVOStYmrGUuZFzWX5kOQA+eh8ujb+Uh9Y9xL9m/4vX97yOn8GPhckLRYK505jqpmqe2PgEmws3A8rzd1b+LJ6e8TQmXUcsqiRJvLTjJZrtyo7IypyVvDjnxS7b7E2WH1nOExufaD9ekr6ED875gBivmD7vi6D/EEbIKSLLMkU1jfh2IyakUOyECIYYST5JPDr5Uax2KxmVGe0GSBubCzeTVZ3FmIAxNFobeXvP2w7nW+wtrMtb120jJL8un7f2vuVQVtRQREZlhjBCBIOegtoC3j/wvkNZfn0+HlqP9uOKxgq0Ki01zTVUNVXx5vw3UUtq1KquJeIFpwfZ1dntBkgbv+X9RnZNtkOQ+caCje0GSBtv73ubKcFTMGgNfdLXsoYy/rfrfw5lNc01HCg/IIyQ0wxhhJwipXVNGI6TI6QNH6OOEpGwUDAEaQtkPFYsiCx3JMGyys65cnqUZ0QGO873sdtFHIpg8CMjO/xeOpd3dWyX7cKHXwDQrecvgM3u/Ly12q1OY6w3kZG77G9Xz3bB0EYEpp8i+ZXHzpTeGZNeQ2OLncYWkdhNMDSJNEeSEpjiUDbKbxRRnlEA6DV6bhpxk8N5taRmeuj0bt8j2COYhUmOmvY+eh8SvBNOrtMCwQAi1COUBQkLHMr8Df4OiQrNOjPIYNQYhQ+9oJ1oz2hG+Y9yKJsQOIFIc6RD2dTQqWgkx/Xnm0bc1K2YkLzaPD5K/YhFvyzi7b1vc6TmyEn11d/oz6JRixzKDBqDGM+nIWIn5BTJr7KcUBkLFD9MHw8dxTWNRPq690HPBIK+RUJiXsQ8ErwTOFB+gCSfJCLNkUh0BJ1PDpnMf+f+l0/TPsVT58mVSVd22xULlODb64ZfR5RnFN8c/oaRfiO5KPYiws3hvfGVBII+RavWcvPIm4nzjuP7zO/bDfv8unzGBYwj2jOakX4jOVh5kLfPept47/j+7rJggOCl9+If0//Bz9k/szZvLbPDZzM/cn57PF4bI/xG8PZZb/Np2qdUNVdxVeJVTAiacML265rreGbLM6zOWw3ApsJNLD+ynP+d8T98DD497u+50efi7ebN0oNLiTRFcnnC5WIx6TREGCGnSH6l5YTxIG20JSwURohgKJJdk80/t/4TX70vMV4xrMxZSamllBF+IxijHwOAu9ad2eGzmRk286QTGgYYA7gs4TIuib9EJEUUDDkC3QOZGjKVFdkr2Fa0ja8PfY1BY2C473DOjjqbicETxbgXdEmkOZJbR9163ISxKknF2MCxjA0ci122d3ssHak50m6AtLGvfB9ZNVknZYR46705N+Zczo4+W4zn0xjxf/4UyalowNe9e0aIt1HZCREIhiJtOx7ljeVsLdpKqaX0mHVVMtCF73tPEC8uwYCgCx/7U0VGZkfpDvLq8gCwWC1sK95GvbVejPvTGbu9W8/N7o6RHo2lY6ioS8c60U3EeD69GRD/9yVJSpQkaVenT40kSff1d7+6Q25l99yxALyMWpE1XTBkiTRHMiV4ikNZSmAKUeaojoKmWkj7ET68DJbeBEc29MokTiDodfK3wzd3w3sXwp7Pob78xNd0kxD3EG4YfoNDmZ/eT7irnK401sCBb+HDS+DLRZCzWTFI+pBIUyRzwuY4lI3yG0W0Z3Sf9kMwtBgQ7liyLKcDYwAkSVID+cBX/dmn7lJQacFvRFC36noZdBRWi6zpgqGJ2c3MY1MeY3XeatbmrWVayDTmhM/BS+/VUenwr/DZdR3Hqd/AjcsgfGKf91cgOGmK98N7F0BzvXJ8ZB2c8yxMus0lzatVaq5OvJpIcyQ/Zv3IMN9hnB11NuEmEft0WpKxTDE+2jjwNdz0C4SO67MueOg8eHDSg0wJmcLqvNVMDp7M3Ii5eOu9+6wPgqHHgDBCjuIM4LAsyycnu9CHyLJMQbUF/27uhPi4a0kXCQsFQ5gwUxgLkxeyMHmh88mWBlj/H8cyuw0OLhdGiGBwUbC7wwBpY+3zMOxiMAW65Ba+Rl8uiL2AC2IvcEl7gkFKYw2s/Zdjma0Fstf2qRECinrb1clXc3Xy1X16X8HQZUC4Yx3FVcAnRxdKknSrJEnbJEnaVlp6bF/zvqTGYkUC3N26Z8t5u+uEO9YQYyCOy4FIfWM1VhlQa0HjRnPMbKzhk0CSlDKByxFjsxdRdfHqVGlApYaWjme8LMsO8rqdOV55V7lChgpiXPaQYz0j22R2Wxr73DWrO2O0ydpE/dGGukBwFANqJ0SSJB1wIfDQ0edkWV4MLAZISUkZEE/o3MoGAsz6btf3MeooEoHpQ4qBOC4HEpllaawuXM8vR5YrMoxnP4mlLIO385ZjUgdw3fgrGRc4YWA9iIYIYmz2IiFjQO8FjVXKsZsJzv8PrHgCivfB2N+REZnCF1nfs6tkF+dEn8P8yPmEmELIrs7mu8zvWJu3lplhMzk/5nyiPKPIr8vnl+xfWJa1jLEBY7ks4bIhKcErxmUPcTPBzD/DZ512l7UGiJwCm16DPZ9C8BhIuQmCRx2zGVeQU5PDD5k/sDpXcce6KO4ipwznVruVTYWbWJK2hIrGCi6Ku4gZoTMI9gju1b4JBicD7d1/DrBDluXi/u5Id8ivsuDfTXleUHZCyuuasdtlVKpTU5QQCAY6zc2NfHroCz5J/xSA/eX7WZu/lsemPMb20l0ArCnewrtnvcvYfuynQNBj/JPgd98pwcKVWTDuOvjsemisBiA/dha3r36fUksZAAcqDpBRmcEfxv+BB9c+yIHyAwCkVqSysWAj/5nzH/6z/T8sy17WXn9lzkreP+d9MXkTQNxcWPgl7P0M3ANg5ALY+T5sWaycL9ipxIncshJ8Y3ulCzVNNTy54Um2FG8BlDG6Jm8Nb8x/Az+jX3u97cXbuXvV3VjtVgD2lO3hgZQHuH749b3SL8HgZqC5Y11NF65YA5W8Sgs+3YwHAdCqVbi7aSirb+rFXgkEA4Os6sMsPfiFQ1ltSy2VTZXtx3bZzrqCdX3dNYHg1AkeBWc8Cpe/BZaqdgME4LC7V7sB0sb3md+TVZ3VboC0sadsDwcrD7YbIG0UNRRxuOpwr3VfMIjQuUPcGXDJ6zD/KdAZYdvbjnUslVCS2mtdyKnJaTdA2jhUfYismiyHst2lu9sNkDY+Tf+UwrrCXuubYPAyYIwQSZKMwJnAl/3dl+6SW1GPn3v3jRAAPw8RFyIY5FibnINyO2GX7dQ116GSVGhVzr7MWpWWmWEzmRQ0CbWkxk3ds9+QQDDg0HtD0nlgVJK2abrY6FZLajSqrp0PNCoNaknt3KxGT31LvdOkTnCa0lyvPH9VaiUG6WiOMb5cgVrlPD4BpzGtUWlQSSpSAlOYHT4bd607OrXumNcLTm8GjBEiy3KDLMu+sixXn7j2wOBIeQP+pp5NoLyNwggRDFJsVshcA59cBe+cC7s/hYZKhypZ1Vn8e/u/ufbHa9lUtI0bhv/O4fw5UeeADGUNZVhlK39M+SMzQ2f25bcQCFxL3jbY9iZUZsOYhTDmGuIqCoj3dHSLuW7YdcR4xjArbJZD+bSQaZQ0lHBV4lUO5b8f/Xt2l+5m4Y8LeWTdI+wv29/b30QwUGmogF2fwDvnwCdXQ1UOnPFXxzre0RA4vNe6EGGO4JzocxzKJgZNJNrsmCckJTCFByc8iFpSU1hXyLXJ13Lv2HsJMAb0Wt8Eg5eBFhMyqMirtHDmsO7lCGnDx11kTRcMUgp2wAcXgdyqxPLVbXDxqzDmGgAqGyv5y9q/tLubPLv9Wf6U8if+Pu1vrM/fQKxXNP7GQB7b8Fh7kzuKd/Du2e/29TcRCFxD8QElX0hLQ+vxfpj8ewLizuTfPreyoXgbB8oPMD1sOikBKXjqPXl40sPMCZ/DhoINRJgjqGmu4aF1D7EweSFPT3+azYWbmRIyhZ0lO/m0NZ7qUNUh1uSt4ePzPhbJ4U5H0n6Ab+/qOM5aDdd/Dws+gIyfIXAYxM8Hr97LI2O1W4k2R3PbqNs4XHWYSHMkOpWOFnuLQz0Jiee2PodVVnbv0ivTeWTSI73WL8HgxqVGiCRJCcADQGTntmVZnuvK+wwEZFlWAtN7uBPiadBSUCWMEMEgJPO3DgOkjQ0vQdL5oDeTU5Pj5O/+/Lbneffsd3lm1jM0tDRw47IbHc7LyKzNX8u4wL7VuxcIXELx/g4DpI3t78GUu4j0DCPSx1ndKsQjhETvRN478B5r89disSoJbD9M/ZB3z3qXp6Y/RU5NDo+sc5y41bXUcbDyoDBCTjcaq5XnbGfsNsjdBDP+AMMu7JNu5NTk8MruV9Cr9QR7BLOhYAMN1gYmBE/A3+jfXm9X6a52A6SN9/a/x9nRZ+Pl5tUnfRUMHly9E/I58BrwBmBzcdsDimpLi5IjRNczP0dfDx35VSJrumBgYLPbqGuuw6gzdhm/4YDO2EWZSfFPpsM3ONYrlkTvRA5VHSKjMgOjxkh1VQ5qnQceOg+nJkxaE1WNVdhkG74G31P+TgKBy2muV3Ix6E2O5e5+MPxSyF4D9a2B6FqDksOhoRKMSjZpq81KfUs9JjcTKkmFWqUmq7ojoDfKHMUw32F4u3lTVFeEWlKjU+uwWh0nczp199UYBUMESa3I9B6NtvV53FCpPJs1x1kQtTZBc0P7eASwtFiwylZMui7a7oK253uwRzDJPsnoVDrSK9Od3htuajfUkppJwZMwaU1sKtqEUWtELampb6lHQsKo7XiX1DTXoFPp0Gu6n+5AMHRwtRFilWX5VRe3OSDJrbAQaNYjST2T2vVxd2P7kcoTVxQIepms6iyWpC/ht7zfmBg4kYXDFh4/L0H0TOVl2FTbUTbrz4pyC8pE6m9Tn2J94Qb2lO5huN9w7h5zN+uyV/D1kWXEmcK5NukqthZtRUZJDzDcdzhhpjB+v/L3WKwWFiQsYE74HCFLKhgYtDQpBsZvz0JTDUy9BxLPBb0n5G6E9S9CdS6MugoayiH9R7j4Ffjpz1C8F0ZfQ3rSmbyX8Rk7S3cyL2IelydcTqQ5kotiL+Lbw99y26jbKKgvIMocxcfpH7O+YD1J3kn8ffrfeXjdw+07JZGmSBK8E/r5DyLoc9w8YMaf4NNOWcrdzBA2EVY/o+QJCRwB0++D0PHO1+dtgzUvQFkajL6GltFXsaU+h9f2vEZtcy2/G/Y75oTPwUvvddxuRJmj+Pu0v7OxcCO7SneR7JPMtcnXOu3MpQSk8MCEB1iWtYzCukIuj7+ciUET2ViwkcV7FqNWqblt1G0k+iSyKmcVn6V/Roh7CLeOupVxgeN6PKcSDG4kV2RmlSTJp/Wf9wAlwFdAuw6tLMsVp3yTTqSkpMjbtm1zZZM95se9hby3IZv75vXspZBfZeHFFRmsfXDIeagNVbr9RBwI47K7VDVWccfKO9hbtre9LNwUzrtnv3v8AMLCvXB4pSIHGT8fQlNAq6zAVdTksujXe8moOthePcocRUpgCksPLgUgyTuJ+8fezZaSHbhr3UnwTuCuVXc53OLRSY9yZdKVLvy2Q5IevakH09gcUGSvh3fPdSy79A3wS4C35oGtkz/8tPsUhawPL1MMFqBgxr0sLF9HqaUjM/jUkKm8MOsFGqwNHKo8xGu7X8Nd596e5K0NH70PT017ip+yfmKE3wimh0wn0jOyN7+tqxiSz8x+Ze9SqCmA0jTFKAkcCUc2wO6PO+q4mWDRr+DXaSGpJA3enOugZrj9qne4cfMT7QtBAH+b9jcuirvouF3o8p3hEc675zi+M/aU7uH6n67HJnc4w/xx/B95Z/87VDQqU8EQ9xAuiLmA1/e+3l5Ho9Lw0bkfMcx3WPf/Lj1DWDcDEFepY20HtgG/Q4kJ2dBa1lY+5MipaMCvBzlC2vB111Fc24QrjD+B4GTJrc11eJm0lWVXZx//wuCRyorbmU9C1LR2AwQgp+qwgwECkF2T7ZDIKq0yjdq6Au4bfx+LRi1ifcF6p1ssPbiUqrZM1AJBf3LwF+eyTa9C0R5HAwRgx3tgbWw3QACy3b0cDBCADQUbyK3NJcAYgJfei52lOxnhO8LBAAGoaKygpKGEnSU7CfMIGywGiMDVNFbD6qdh+f9B5mrY+zlUZSs7IJ1pqlWMjs6UHHCUU/cIZEPpLgcDBOD9A+9T33Js2XWAnNoc53dGXS5Hqo84lO0q2eVggICSJ2RayLT249nhs/kk3TElnNVuJaMi47h9EAw9XOKOJctyNIAkSXpZlh2iriVJGpKOfkfK6wnoYVA6gF6rxk2joqK+Gd+TMGIEAlegU+uQkJxeRiflc95sgZZ6dOquf+qqo9Y6dKqOe3Tlj2zWmk8cnyIQ9AUGL9DolV0/rR4OLgeDd9f+93pPJRakE7ouFl/b4j1AyZmjklTYsaNRaZzygWgkDfl1+cfMLyIYwliqFSEQjU4Zc+5+EDW9NT7JpsQeHZ2v6ehxeXSchbUJk8bgdCsvN68u89R05ljvDK3a8VndOd6jDQ+tBw3WDgGHBmsDHloPapprHOq5HS+uRTAkcXWekA3dLBv0nEyOkDb8PNwoFLlCBP1IpDmSBQkLHMrmRswlxjOmZw3lboEl18LrM4isLuaiyLMcTs+LOIM9ZXvaj2M8Ikjs5Nc+LWQaHtqOYHWVpGLhsIW4t8aZCAT9Sux8mPsIVByG3K0w/kYlLqS+HExHybPPe0LJ1RA0suPyolQmBTj66V8/7HoiTBEARJgiWJi8kF9zfuWSuEsc6o3wHUGDtYFhPsNELMjpRHM9HPgW3j5LcaXa/w2c8RiMvgZyNys5QryjYdaDjtcFDoego/KEBI0Ev8SO48YqpgSmOD1zF41cdMLA8ChzlNM744yIM5zeGWMDxuLt5u1QtmjUIjYWbGw/XpO3hjvH3OnYfWNgb7piCQYorooJCQJCgQ+Ba+jwvTMDr8mynHTKN+nEQPAjnf7MKu6bl0Col/Oqwol44Zd0Fs2M4azhPcsxIugXhqx/c1lDGTtLd7K/bD+JPomMCxhHoHtg9xsoTYc35nSsxo29jtKISezUqThQfZgkcwwjjCEckS1sL91FqHsIKf5jiAwa69DM9qLtbC3aisVmYULQBMYHjsfQxWqdwAERE9IXZK1R8oB0Zs4jsPl1SLkRbM3KqnTCWUp8lM4IFVlwZD2UH4bIKRT4x7OjfD+Hqg4xyn8UY/zH4GPwaW+u3FLOrtJdlDeUo1MrikNhpjAiTZGUWcpICUohzBTWx1/8lBiyz8w+4fAq+KCTQWr0gWl/gOWPdpRJEty0HBor4chG8IlV3GN9upBvLj+sxDZVZUPkVAibSHpDIVuLtlLfUs/E4ImM8BvRrd3no98ZYwPGEuTuPI85VHmILUVbqGqqYmKQ0v7BqoNsLtzcrpwV4xnD7tLdbC3air/BnwlBE4jx6uEiWM8QMSEDEFft8Z4F3ACEAf/qVF4LPOyiewwYrDY7xTWNJ+WOBYpMb6GQ6RX0M35GP86MPJMzI888uQZKUh3dAczB+H9zF/M1eub7JUBZBlgbCbvhR6ZNPnayqvFB4xkf1IWqi0DQ3xxc7lyW+h2ET4A1zynKcD6xSlB6m4S1T7TDZDAECPE6dm4PX4MvZ0Sc4dp+CwYv+792PI6ZAzvecSyTZSU+ZNYDiqvg8fCNVT6dSNSbSfRJPMYFx6a774w47zjivOMcykb6jWSk30iHsknBk5gUPKnH/RAMHVwVE/Ie8J4kSZfJsvyFK9ocyBRWN+Jl0KFVn5w3m49RR54wQgSDFUuVsgJ8tO+vpPweqmY/SEnoGAIK9+H1y/8pvvRHUWGpQC2p8dR79kGHBYKTxN3PuczgDY2tvuzN9cqE8BixVA0tDdS31GPQGGhoacBb7+3gQ99sa6a6qRqTzuTgDmO1W6lsrMRd696lj71gCONx1G50U40y5o7G4K3swtWVgpt717lEjkN1UzVWu/W4uZmsdit5tXmYdKbj1msb5956bxG/JOgRrh4tkZIk/eGosmpguyzLu1x8r37jSHkDQZ4nH2/vZ3LjYHGdC3skEPQBLRZFnnfFX5UX4znPQPAYKNylnM/fyfbblvPugQ/YuflLRvmN4qZbfyGlU9boisYKfsz8kXf3v4tRY+TusXczI2yGSFQlGJjEzYO1/4I2tTaVGpIvUPKAgOIWM+chMDgb03tK97B492KmhU5jZc5K0irTmBM+hxtH3EiMZwyHKg/xxt43WF+wnvEB4/n9mN+T5JPEkZojfHjgQ5ZlLyPeK557xt3DmIAxffaVBf1M8vmw+dWOfEzZ6+Cyt2DJQiVQHcDoCyFj4eeHFbUsvySY9xhETD5h843WRtblr+OlHS9Rb63nhmE3cE7MOfgZHA3u9Ip0lmYs5ZcjvxDsHszvR/+eaaHTnIyM3SW7eWnnS2RUZnB21NksHLaQSLNQchN0D5fEhLQ3JkkfAynAd61F5wFbgSTgc1mWn3XFffrbj/TDTUdYnV7CzdNPzn8xo7iWz7fl8v09M1zcM0EvIPyb28haB++d13EsSXDlR8pqcFUOh5LO4p51D5Jbm9teJdg9mP/O/W/71v/SjKU8ufFJh2bfnP+m2JLvOSImpK8oPgC5m5RxHjAcSvYreXKa68EUDDoTTLzZ4ZLs6myu+uEqrky8ki8PfklVU1X7udH+o3lu5nPcvuJ2Mqsz28sDjYG8e9a7PLvtWX7N/bW93KAxsOS8JUQfx6VrgCGemadK0T7I2ajsOEdMgYARULQLcjYpiQrDJyiJMvcs6bhGa4BFqyHg+CG4Wwq3cPMvjuP1scmPcUXiFe3HlhYLT216iu8yv2sv06g0vHHmG6QEpbSXZVZlctUPV7Un1ASYHTabZ2c+i0E74OL6REzIAMTVOyG+wDhZlusAJEl6HFgKzETJGeISI6S/ySqrP6kcIW34ebiR3xN3rLoS+OVRKN6v+IfOfrDHW68CwSmTvdbxWJZhxeNwy0rQe5KTs8rBAAEorC8kpyaHRJ9E6lvq+STNURseYF3+OmGECAYugcOUD8DGV5RnscYN1G7KjqApGIZdAB4dCduya7Kpb6lHp9I5GCAAu0t3c6TmiIMBAlDcUMzh6sMOBgiAxWohsyZzMBkhglMlaITy6Uz4ROUDUHYQ9n7meL7FooiFnMAI6axS1cbHaR9zbvS57aqEubW5/JT1k0Mdq93K4arDDkZIVnWWgwECsDpvNQX1BcR6OcahCARd4WojJAJo7nTcAkTKsmyRJKnpGNcMOjJL6xgd7nXS13sZtdQ32bA02zDojq/NTWM1vH02hIyB8TdAxjJ4cx7c8CO4H9tHUyBwFaUNpaglNT7mUDCHkj/7AVp0RiK2vI1KYwRrM1TnH1PRykPrQVF9EW4qN8Lcw6hprmF22GwabY2sylnl5AYgEAwY6koUF5g2OV596+KPtUn5ALgHwFFjv+23oFY5P981Kg1uajckJFKCUkjySSLQEIiPwYcAYwBmndkpf4JRI+JCTjuOHnud0bgpO3BNjuOEbkib+xp8MWlNnBF5Bnq1ntV5qwk0BqJRa5RnvUqNm9oNTzdPyhvLHa41ao00WhupaqrCrDNj1BrRSBpmhs8kxD2EnSU7yazORK/WU9VYRZOtiQBjAJIkNiEEXePqPCEfA5skSXq8dRdkPfCJJEnuwAEX36vfyC5vIMh88j7sKknC3+RGflXDiSsvfxz84hV9ev8kmHovBI6AT65yztgrELiQcks57+1/j8u/u5wF3y9gXUAkX533JDdnLWHhvv/y0qizyJr3MHx0OfxvIgk1ZU65Di6KvYjUilQu/uZiblt+G5cmXMLFsRezLHsZmws3c8PwG5gadGI/ZoGgT2msgZ0fweJZ8No02Pg/OLRSmRiaQzvqSSqY93iHcdJKnFccU0OmklaRxpTgKQ7nLo+/nG1F23h+1vNoJA1LM5ayOm81Nc01vLDtBZ6d+Sz+Bv/2+imBKcR7xyM4TXAae69AfaljHa8IJXdIZ0InKLlCTsCU4CncOPJGthRuYVn2MuaGz2XRqEV8kvoJl317GVd+fyVpFWncPfZuh+vivOKINEfy5zV/5sKvL+S+X+/DrDPz+JTHKaor4ouDXxDkHsS/Z/+btIo0rv3xWi799lJe2fUKxfXFp/pXEQxRXLoTIsvyU5Ik/QRMQ/G/u12W5TaHz2tdea/+wmaXya+ynFJgOkCAyY3cSgtxAcdxq6rMhv1fwcWvdpRJEoy7Hlb9DVb9Hc584pT6IRAcizV5a3h+2/Ptx9UtdTy26a/tx2/tfweDxsBtVgs01+H76UJuuO5zJgZNJKc2hyhzFEV1Rfx7x78BSK1M5b7V93P7qNupaqqiqqmKl3a+xAhTJPG+PZeLFAh6jZyN8M0dHcc/Pwyz/gyb34AJNykB6ho9RM1UdqmPwtfgy1+n/pW9ZXux2W1cFHcRqeWpmN3M7CzZSYu9ha8Of9XuvriteBvZNdmcHXU2D659kP/O+S/7yvcRZAxipP9IsVt4OuE09h4CgxeMuaajrLkBqnIVQ6ShQnHPtlQosUrm4OM2X2op5aUdL7Uff5z2MYHGQN7e/zbVTdXQBH9a8yfemv8WL899mfTKdHz0Pgz3Hc5f1vyFzBrFjXBj4UYmFExg8Z7FNNqU5Msrc1bS0NKAWqUmpzYHgNf2vIZOrWPRqEWu+fsIhhS9oaW2Eyhoa1uSpAhZlnN64T79QkGVBU+DFjfNCdyoToCfSUduxQl2Qja9CvFnOsd/SCqYejd8dy8MuxBCx51SXwSCo2m0NrIkvSPoMc4zjn1l+5zqfZ/1I5eMu56An5U8IDEfLiDmzq0Qez45tTk8tO4hh/pWuxWr3epQtr5wI1OiT6B1LxD0JQe+dS47/KticKx9QTFCfONh/E2g7jrJW6B7YHvyz1+yf2FJ+pL2ydrto253ip8qs5ThofWguqma4oZirht2nUu/kmCQkPqdc9m2t2HE5aBplYKuyYcNLyr/1hrA2qjE6EVM7YhfOgYbC51jQr7N/JYJgRNYkbOivWxFzgoenvQws8JnAUosU5sB0kaTral9THdu/7ZRt7Euf1172ZL0JVwWf5lDkk6BAFxshEiSdDfwOFAM2FB2Q2RglCvv058cLq0j+BR3QQD83N04Un4cI8TapChfnPNc1+cN3jDud/DdPXDrb8pLUSA4mtoSsDcrwbNdjJEGSyVVllLMbt54uHe4gGhUGsJN4VQ3VTM3Yi4aSYNJZ8LTzZP5kfMxao2szl2Nv8EPyehDwaw/4Zu5Breyg8oKMaBX6/Fy86KiscLhnirJ0Qs00BhIeXUOLbZmAr1ikFQqqhqraLA24G/wd8irIBD0Cd5RHf82+sLwSyAgGTJ+UcrsNvCOhJZGqMpT/PbVGqpq8mloaUCv96JRbsGgNmCxWfA3+DtO1iTld2Bvk1xtxd/oj0bSOOUGabG1UGopxaAx4K3vImeEYOjgFamIHAy7CFRaSPteSYjZWRpXowe9F03DL6I8fh7Gqjy8Vj+jLFg21So7IgbvLgVsAowBzmWGADQqDdcPu54mWxPLjywn2N1xR8WoMTqNWbXk/E5x17o7GSbB7sHoNXqK64uRJKm9Dy32FkobStGr9cJAOU1xdUzIvUCiLMvDZVkeJcvySFmWh4wBApBZWu8SIyTArCe7vP7YFQ6vAs/wroPS2oidq6x+7PzwlPsjGGI0N8DepbB4JrycAiufhOo8hyrpRdu5b/X9nPv9An6/6m72FmxqP6dRabgu+TpmhM3gi4Nf8NWhrxgTMIbrh13Pr7m/8ln6Z0wInMBto27j9szPOS/3Sx6LSCD7qvfBKxxQXnYPTnjQ4Z6j/EZSZilrP/bV+xLpncBly67nwp+u4b3dr7MmZzXX/3Q95311Hk9seIIj1Ud68Q8lEHRB0rnKJC5qOky4BQ58A8sfA88wGH21Epc38gp4Zz68PA7bxpfZkPUL9659iFXFm7lp+SLO+/I8HtvwGN9nfs97B97jH9P+0W6Ar8lbw9WJVzvc8qzIs9hftp+/Tvsryd7J7eU5NTk8tekpzvvqPBb+uJC1eWuddhMFQ4jEcxSX631fws4PIPFcmHgrqDpN17zCybpuCY8Z4bwtj3ND4TI2LXgd2T0APr4SXhoDn1wDhXucmh8XMM7BvU+r0rJo5CK83LxYmrGU5UeWc2XClUwPme5wXaQ5kltG3OJQ5uXmxdSQqQ5l9467l90lu9uPNZKG+8ffz5L0JVzyzSVc+u2lfJL2CdnV2Ty75Vku+OoCrv7halblrKJFxLmedrg6T8ivwJmyLPfqE7I/tcUf+nIPOrWKs0cc3+/yRGSW1vHuhmyW/2FW1xW+WKS8BJMvOH5DZRmw+p9wz05w8zilPgm6ZHBq3h+d0wNg7qMw8wEAyqqOcP3K28mt6zBMvN28+eTMNwhtjc/4PONz/rqxIwbkD+P/wL+2/8uhyRuH38i3h79tV1GZEzabZ2Y9264O1Ght5ED5ATKrM/F282aYbzJVNXmkV2agU2nxM4Vxx+p7abIpSkN3j72bV3e9irXTI+SsqLP4+7S/46Y5eVnsIYjIE9LblKZD0V74wjGnAvOehNCx8P5FyiIQkHrtx1yz8VFuG30bi/cspsXeMZmaEDQBrUqLxWrh9lG3k1GZQahHKIk+iWRVZ7G3bC86tY7U8lRW5KzArDPz5vw3SfZNptnWzJMbnuTbzA73MLWk5qNzP2K434mDkPuJwfnMHCik/6QIz3TmwpdhXId7nqWxij/99gBrihwXjpZM+QcJH3a61jMMbl7hECeyMmcl+8v2o1Vpsck2zDozVru1PXavjVfnvcr0UEdDpLqpmgPlB8itzSXEPYRhvsNosbdwoPwAZZYyoj2jGeY7jHJLOfvL99PQ0kCiTyKHqw/zyLpHHNp6ZNIjPLPlmfZnvYTEB+d+wGj/0Sf1Z+sGQqJrAOLqmJBMYLUkST8A7ZK8siz/69iXDC4OldQxLznwlNsJNOvJq7Qgy7KzfJ3dBoeWw7kvnLghvwRFEWPDyzDnL6fcL8EQIW+Lc9n29xSVNXc/8muyHQwQgMqmSnKrswj1TaTR2sjSjKXt53z1vuTUOId2rcpdxYSgCSzLXgbAr3mrKa4vJsozCgC9Rs+4wHGMC+yIWwr2CCE5RNG7f279k+0GCECzrdnBAAHFn/6esfcQYY7o2d9AIDgV/BOV38zR7P0M/BLbDRCArKZyrLIS79TZAAHYWrSV20bdxut7XsfP6MfU0I6V4/y6fN7Y+4aDi0tNcw1Z1Vkk+yZT2lDKD1k/OLRnk21kVmcOZCNEcCqkfu9ctuNdGHVle0xIUU2OgwECSrxdVmMZCZ0Lq/OgMsvBCNlUsIlP0z8FlIn/zLCZFDc4q1etyVvjZIR4unkyJWQKU3BUfGuLfWrDqDUSblZ2xO2y3UHgpI11+euI844jrSINABmZQ5WHetMIEQxAXO2OlQMsB3SAqdNnyJBZWk+o16lnAnV306BVS5TWdZE+pWAn6L0dkl8dl9HXwOZXFJUMwemL3a4oplTngakLQ9krSgliBNx1Hl3683rozICyqhZljmovb7A24Onm6VQ/0BjooCXv5eaFXtN9d8UQd0d3Q61Ki7vWnUvjL2XRyEWMDxyPr8H3mDlIBIJeJWo6TLsXfDslXvOJBX2n34Lek0BzJItGLsLc+vvpjFlnpsHagFFjbB/HNU015Nbm4qXzwk3lvMPX1o5eo+9SGaur+wiGCD4xigz0lDs7xp5fokNMiF5j6PJ5bDr6OSmplAzrnQh0D8TP4Me1yddy04ib0Kv1BBmd3b7DPMJO6WuUNJSQX5uPTbYR4xnjdD7YPZjKxkqHMrObGNenGy41QmRZflKW5SeB59v+3Xo8JKhuaKGh2YaPu84l7YV4Gcgu6yI4/fCqLmUfj4k5WHlZrvvPCaseqjzEY+sf4/fLf8+HBz50WrUTDFJqi+G3Z+B/E+CVycqLx7vTg1+tgzkPtSezivRJ5vfJ1zs0cXXMRUT7KK5YGpWGhcMWtk+aLFYLIe4hhLiHtNfXqXRclXgl24o63Cn+Mv6PBLkfJ47pKKYETyawU06EJlsT9427j40FG3lz75sYNAaenv40/kb/47QiELiYhkolP8NXt8Lm1yF6Foy+SjHiI6fAga9g9kO0+Ceycv4j/HnzX3lr31s02ZqYfFTem4XJC/kp6yf+mPJHwjzC2Fu6l1uX38q5X57LU5uf4h8z/uFgZJ8TdQ6Jrb9DX4MvD096GKmTJ8m4gHEk+Rw/K7ZgEBN/Foy8HHZ8oIy9qJmQcotDTEiwTzx/GX2Xw2XTAsaTqDtKtGD6H8EvzqFoStAULo+/nO8Of8f7B97HoDVwdfLVDmPQ3+DPtNBpJ9X9hpYGvj30LZd/eznnf3U+z2x5hovjLsZd25FI0cvNizMizqDU0pH/JNE7keG+YnfvdMPVMSFTgLcAD1mWIyRJGg3cJsvyHSe4tEf0lx/p9iMVPPTlXp68cIRL2nvtt8OcNzKYBRPCHU+8fY4izRs2ofuN1Zcqkr337AT3rjXlf835lUfXP8qZkWcSaAxkbf5aJEnitXmvYdINqQ0rVzI4/Jt3vA/fdkoupdLAtV9AUzW0WBRln6BRSp6ZVmrrikkt20t+XQGBxgCG+Y3Eq3MiNuBg5UEyKjPQqDQY1Aa2FW9Dr9EjyzIalQajXSYOLcUt1UShI7kkE7f5T3Urc28bOaX7Sa1IpdnWQrBXFDevuN3BPWVuxFyemfFMj3ZYTgNETEhvkvoDLLnGsWzek4AMG1+G+jKY/RB7Y6Zw7a93I9PxHn0g5QECDf7UWevxNfjRbG3Gz+hHsm8yVY1VXP3D1Q67h/4Gf56Z8Qzplen4G/0Z4TOC0E6/wxZbC6kVqWRVZ2HWmUn2Te6Rod8PDI5n5kClq7F3/ouQckPHcVMdjRv/R1pIMtmN5Xhr3UluqCMgaAw0Viu74V4REDxayTHSifX567l9xe0OZQ9PfJjxQePJqMhAq9aS5JNEpDnypLq/pWgLN//sGEd126jbOD/mfA6UH0CSJJJ8kgg3hZNWkcbhqsN4aD0Y5juMYI9Ti7U9ASImZADi6piQ/wBnAd8CyLK8W5KkmS6+R7+RUVxHiAtcsdoIMLuRWVbnWGhtgsKdMO2+njXm7g/RM2DDf+FM582n9Ip0Hl3/KPeOu5doz2gAxgWO4+PUj7l/9f28Pu911ELmd3Bia1FUVDpjt8KuD+GyN495mckjkIkex49viveOb8/W/N+d/+Wd/e84nI8wRfAxwUzZ83lH4eTfg1/3MzxH+A8nwl9ZAfsh8wcn2dJfc36lpKFExIQI+o60LvzyU79V3LDqW9Xddn9CZmiigwEC8O/t/+aHS38gxCPEqYl9tfscDBBQksdJKomFwxZ22RWtWsso/1GM8h9SQpOCY9HV2Nv5vpKssC1PSG0B+tX/YAwwpnO9K95V5KSPw6bCTU5ln6R/wvkx55PgndDFFT1jb+lep7KvD33NNUnXcG7MuQ7lI/xGMMLPNYu6gsGJq2NCkGU596gim6vv0V+kF9US4uk6IyTYbOBw6VFGSMFO8IwAnbHri47H8Eth+ztgqXIobrG38OCaB7ki4Yp2AwQUnfqrk66muqma9w+8fxLfQDAgUGkgoIsHuX+yc9kJsFgtHKk5QklDidO5zq5YbUQbg9DXFHYUmEOollRkleyhqragx/fvys/Z3+gvYkIEvYfNChVZUJnTEWzun+hczysCaosU2fTJv4cZf8RT0/GcNuvMXJl4JXeNvQutquvcNiY3k4NrFSjPYYPaQHZ1NhUWEdd3WlJTAOWHodmiiM0cTeAIWqyN5BTtorBkP7h5KflrjqYbOWTCPMIIcg/i+mHXc8vIW0j2SSbWM9ZlO81d5SGJNEeKnWxBl7jaCMmVJGkqIEuSpJMk6U9Aqovv0W+kFdUQ5u1CI8RLT2bpUblCjmxUXGdOBo9AxYVry2KH4s/TP8egNTjpeQOoVWpuGH4Db+x9g6L6opO7r6B/kSRlq75zsKxHkJLroAdkVWfx59/+zPlfnc+C7xbwS/YvDrrtKb7DiTR1uA7q1XpuiTgHtyPrlQI3E3sufYWb1v6RC3+6lhtX3M6uvPU96kOSTxLTQjp8kSUkHp74sIgJEfQONQWw4rHWWKpJsP5FReAj4WwlwWcbek8l7s7NBGOvg12fwHf3klySxXi/0USZo7h5xM2szFnJf3b8h8c3PE5mVabT7aLMUdw66laHsltG3sIHBz7ggq8v4Ppl1zvEWAmGOC2NsO8LeG06vDwevlwEUdMc84O5mckfv5C/b/47F/5yA5euuIUlmd9Qd8W7jm0lnqcoZZ6ACUETOC/6PJZmLOXdfe8S7RnNjSNudFlS2DH+Y4jz6ohD0al03DnmTqcEnAIBuD4mxA94EZiH4n/3C3CvLMvlx72wh/SXH+n4p5bz5IXD8fVwTb6CJquNWz/YTupfz0atal0d++gKCBkLUTNOrtHKI7Dicbh/H2gNWKwWzlp6FveOu/e47ixfHfoKu93OP2f+8+TuO3QZPP7NpRlQvE/JjB44EnydFUmORZO1iYfXPcwvR35pL5OQ+PDcDzvcQPZ9TX7RdtLM/jRhI85qJ8E9DOpLoLGaoujpXLXlCSe1rE/PfINQ3+4H0pY2lJJWkUZ1UzVRnlEkeieKrOnOiJgQV7D5dfjpz45lV36o5Gcqz4TivYpkeuBw0BihcAd85ijoUHLBv8jwDuWOtX92cM2aFTaL52Y957SLV9NcQ3pFOoX1hfgb/Pn60Nf8mPVj+3mDxsBn53/WLnM9CBk8z8z+JncLvHWmY9moKyFoJDTXKTtzHgG8Ilfwaqqjy+1r059hmlsAlB9SdkWCRnWtingUa/LWcOfKOx3K7ht3HzePvPkYV/ScgroC0irSaLQ2EusVS4J3gnMqgr6n3zsgcMalMSGyLJcB17qyzYFCeV0TjS2uU8YCcNOo8TJoyatsINLXXXng5G9XMvKeLN6R4BsHuz+FlBv5MuNLYr1iT+hPf3bU2Tyy7hEyqzKJ8er+5FUwgPBPUD4nQZmljOVHljuUychk12R3GCG5Gwnd/BoOoes+MZByE6x5jvzgRCd/96qmKvJrcntkhPgb/cXOh6D3aWmEXR87l2f8ohghvjHOhnzq107VA379J1vnP+QUG/Jb3m+UNJQ4BfiadWYmBCmiI/vK9jkYIKC4RObV5g1mI0TQXcoynMv2fwnmEFinJA+sOueffJu3yqnarrI9TJv0FwhL6dEttxQ655D65vA3LEhYgMnNNQI1IR4hXcZECQRH4xIjRJKk/wLH3FKRZfkeV9ynP0kvqiXKz93l1nyYt4FDJXWKEVJ1BJDA2LW6VbdJvhA2/Bfb2IW8f+B9bhhxwwkvMWgMnBFxBov3LBa7IYOUlmYL+VWHkJAI80lArem+wWzUGgn1CCXvqASGXjpPKDukyEMGjXS+MHgM6L1g5gOY3bwwaoyK+pp7ICUNJSw/shyzm1fPv0x1HjTXKy9jF70YBQIH1Dpl9bhwl2N5V/EgoOThMfg4l4eMI8gcwW2jbuNA+QHW5a9DRibQGIjWZoWSNMW95iiVIgAPrQduajeHhJ0Annrn2CjBIMRSpcQRGbwcXaza6Cquwztaef61YijPJNYjnPy6fIdqocZgautLKKnNx0NnItCn1QWqIgvqSpT7eTsrXEV6RhJuCufMyDPRqDRsLtxMkDFIxGwI+gVXxYRsA7Yf53NcJEnykiRpqSRJaZIkpbZK/Q4o0opqCXOhMlYbQZ56DpW0Bqfnb1degKdq6ASNBEniwJaXMWgMxHrGnvgaYE74HH7L+03EhgxCiioO8vyWf3DJsuu55OfreWX7vymvOtLt67313jwy+RE0Use6xPSQqSSXZMIrE+GVKVCRDeNv6rgocBQknAUrn4A1zxGVvYm/Tf0rO0t2snjPYrYVb+OJyY8R3ZOcBtZm2PclvD4D/jcRPrlKmcQJBK5GpYJx14GhUzCvZwTEzHKuW10Aa56DkgMOfveNYSl8O/pC7tn4OK/veR2L1cJdY+9CJam4NvlaHt/0NzKOrIYPL4NCZ9WgCHMED0x4wKHs+mHXd5ncTTDIKNwL71+sxBotngUZPyuufZ0JHgPRszuO1VqY/xTk72ovctv7BbcNu97BrS/eHE2c/0ju/PVeLv75ehYsv5kVB7+lJXMtfHAJvD0fPrgYDq106tb4gPHMDZ/Lx6kf8+beN/E3+HPd8OuEy6ugX3BpTMgJbyZJ/5Vl+e4uyt8D1sqy/KYkSTrAKMty1bHa6Q8/0j9+tgsvo455ySf2uewJK1OLqWho5l8LxsCyh6G5FkYuOPWGD60gdf8Sfpy+iJlh3VdJ/jTtU0I8Qvhjyh9PvQ9Dg0Hh3/zp7jf4+66XHMqem/R/nJ3U/bFks9s4WHWwPR9BYk0Zfksc/d+59E3FbdBqAe8o5UXXKqlbMO1uripfQ2VTRxZcs87MkvOXEGbqZvbd/O3w5hkdKkUAsfPgyvd7lHvkNEDEhLiCzYuhvhgktbL401QHYZNg+IWO9fZ+AV/cpNQZf6MiAqL3ZFdwMtetdnylzQmfw+zw2by5901ya3MZ7TOcVxs0mMqz4IbvwOi4m9JobSS9Ip38unz8jf4keicO9szRg+KZ2as0VMA750HpgY4ytRZuXQOBwxzr1hZD0V4lp5NfAgQMh+pcJb7PboOAYeAXx+HCrRyuysRNrSPaO5HHtvyD7WW725tRSSo+SbqVYT8+3NG2ux9c/53DPVfnrubuVY5j9u6xdzsJJgxBREzIAMTVeUJOhFMKTkmSzMBM4AYAWZabgea+7daJOVBYw1UTXJ+nINTbwKbMVj/6/O2QdJ5L2q0KGUXIxpeYZQg9tp9cF8yNmMvTm5/mzjF3iu3ZQYK1pZHv839zKl9VsL5HRohapSbJJ0nJxtzSAN+f7Vwpaw1c9F/l3/u+aDdAAAqNZioLKh2q1zTXkF+X330jpPywowECcHiF4tLg270dPYGgW7RYYNdHzu5YY6qcjZD81omyLMO2t5V/e0WSfc5jTs3+lvcbMZ4x5NYqavW7K/ZTEnMtptTvFDWuo4wQvUbP6IDRjA4Y7YIvJRgQ1OQ7GiCg5HOqyHQ2QkyBzgHl3pFOrlSxwROIDVZiiTKLdzkYIAB22U6u3IRD6/VlintWp3t2pb72/eHvuSrxqsFu/AoGIX1thHRFDFAKvNOaYX07iqKWg3atJEm3ArcCRET0bdIyq81OZmk9ET6ul5gL8zKSWVaPbLMhFe+Fafe6pN1NxTvw9o0gKvUncqbf1e3rAowBRHtGsyx7GRfHXeySvgxl+nNctqHR6hlhjmF3qeNLKbmTTGKPUbsprgKFjm0S1EkC8qjYJU8ZTFoTZ0WdhY/Bh8rGSpZlL8Pr6JiQZosS/6TSKLsp6k6Poa7ioTzDRVzISTAQxuaApn2M73IsDxquxEHJdmUiqHHr0rcev3h8DM7jNdIUSVF9Ed5u3pwbcy7ebt5oZQO4B4CY5J0e49LNU5F1bqx2LHfvIgbkJPDQmfEz+FFmKXMo9zp6SqfSON0z2jOaGM8Y5kbMRSNp2FGyA1+9L0aNkNAV9D0uT1Z4EmiAccCrsiyPBeqBvxxdSZblxbIsp8iynOLv37fKOYdL6/E3uaHXuj6juIdeg16rpuBIuvKCctFka33BBhpj5uCbsQJVi6VH184Im8GnaZ+6pB9Dnf4cl525NPYifPUdL5tw91Bmh3bh295dVGqYcItj4KRvvOIa1UbgCBh1VfthZPpKnpjyGOsL1rN4z2LW5K3hsUn/55Agk8ps+PZOeHUyvDoFfnumIwM1KPFMwy/t1A8NnP9v8HBOgCU4PgNlbA5YVCqYcLPzGDf4tsZBTYJlDymr2hFTlfHehpsZpt5DsncCszvltdGqtNw88mZSy1O5YfgN/Jj5Iy/vepl7s5Zy4Mq3wHuITrp7wGkxLr0j4Lx/O8Z3TrxVcbVyAQHeMTw+7g+opY45yYWR80nUHZWscNaDivhCJ8b6jmBy8GTe2/8er+15DTe1GwuTrkajHghr0oLTjb4edV355OUBebIsb249XkoXRkh/sr+gmshe2AVpI9zbQEZGGqG+8S5pr6CukJrmavwDhtHgG4PvwZWUDju/29eP8hvFx6kfk1GZQYL3yUm+CvqWhODxfDD3FQ5VZqBSqYj3TiLE9xT/3wWPgltWQEkqqLTKlr5nJ7cqd184+2kYuxAayinxieCvv91DdZOy+lfcUMyTm/7KcFMk4f6t7gB7PlPcuABszbDmWQgeDcmt49PDH859XvG7t1QoctMnm7xTIDgRDmNcA5IKPrmyI4B421uKYZxyI1z+jpI3pMWi+OmHjsM/ZxNP1lnJSLqFWmxE2SCgNI/ASQ9x+4rbsclKO4dqsnhoxwu8FzAKL71X/31fQd+RfAHc+pviguURAAEjQO+inTBLNdNTV/Hp5L+R01yFl9ZIQtFBvILHwMIvFHUtzwjl2apznLscqUjj47QOaeq1+WsZYY5mVOBY1/RNIOgBfW2EvHh0gSzLRZIk5UqSlCjLcjpwBnDA+dL+Y19+da+4YrUR4mUgI7eQOQFdbPmfBJuLNpPonYgKiaqISQTs+5rS5PO6rbqlVqmZGjKVpRlLeXjSwye+QDAgCPcf1jHZdxU+McrnWBh9IFpJrFmUvbLdAGmjrqWOgrpcpV+NtbBvqXMb2Ws7jBBQjJuY7ospCASnROcx/vECZwWjfV8oRkhXeXjKD+Oz+3Mm7/68o0xS0XDdx+0GSBuZ1ZkUNxQLI+R0QaNTjIDgXoj1qStCs/1tkra/jYP2oG88jLj0WFcBsK1kp1PZsvy1LKy7HrOHa4V3BIIT4ao8Id9x/DwhF7b+991jVLkb+KhVGSsTuNEV/XIVe/OrXa6K1ZlQbwNpRxoh+RR8+DuxpWgz8yIUt5kG/3jU+7/BvTiV+qDuT1CnhU7j6c1P86eUP6FTuy5Bo2CA01CpKLPo3ME7mqqGYg5XZ6NRqUnwSkCjcye3NpcWewthpjDctR2KVV56bzQqDVa7tb1MLanxdmt1d9EaIGQ8lKY73jPAxYZTNymoslBe30yAhxuBnkKEoStqLS3kVjag16qJ9HVHrRpCAjNNdYp7oEYH1iZABSmLlElj5molmzVA+KRjt9GVm6B/Mt5dxIp4unli1omYEFfTYrOTU95As81OuI8BD7cBJDVbV6KIERi8u44rArBZlR22pjpFfMPcjSR/bp5gCobaQsdy9xO7t8V2do9tZYRXLDaVhu3F29FIGhK8EzBoXZuSoNHaSG5tLhIS4aZw3DRuLm1fMDhx1U7I86dysSzLu4Cepf3sI+x2mdTCWm6Z0Xu67RHeBtbXe4BP8Cm3lV9XgKXFQnBbtlJJRXXEJAL3fUVmD4yQAGMAYaYwVueuZn7U/FPul2AQULwfvrodivaA1kja9Ut5Of1jfstfg1pSc2ncJYzwG8lTm57CKluZFjKNhyY91J4ROsI3mb+Mvou/7fxPe5N/HHk70X6t406tgSm/h0O/dMSBBI+B6L7d9ZBlmd8ySvnDZ7upqG8m0OzGi1eNZXKMa4JGhwqHS+t4+Mu9bM6qQKdWcd+8eK6dHIGnYQgsSlRkwbK/KJO+0nQ4tEJxxRp5hXLeHAZjEyBzTUdZVwSPgmEXw4GvlWONHs59lnDPaK5OvJpP0j8BFGP8wQkPEuxx6s94QQeV9c28syGbV349hNUuMzPejycvGk60n0d/d01Ru1x6k2Lo6j3hghch6XxFqreNujLY+b7iltpigaDRcP6/TpwF3RwEF7wES65RVLdAcWHtHLd0DCYGTmCEVwL7qpRs7d5u3lyWdA0Pb3iUdfnrlGd9/KXcMOwGIjxdE8NUWFfISztf4vvM71FJKi6Lv4zbRt1GoLvYeTndcYkRIsuysz7oECGnogGDTo1Z33urK2G6OjLtAdjcvDjV0PetRVuJ905A1Sn8pio8hdhVz6CxVGHtImvvsZgSMoUvDn4hjJDTgeZ6+OUxxQAB8I3jl+It/Ja/BgCbbOPzg0vxNfohSRLIsL5gPV8e/JL7xt2HJElotQYuSriCET7DKKovINA9mDi/4Wg7+yQHjYKbV0JpmpKxOmCY8kLtQ7LK6vn9hzuwtCjuMsU1Tdz50Q6+vWs6od6uT0g6GGmx2lm8JpPNWRUANNvsPPtzOiPDPJkRP8iDiWVZkeYt2KmsTh9a0Vpuhz1LlGDedf+Gs/4Bsx9yjIM6Go9ARThh4iJorFLcYfwTOVy4mazqLO4eezdNtiZ0Kh3fHPqGkX4jifKM6otveVqwI6eSl1YebD9ec7CMjzbl8PC5yaj6c9eurhS+WKQYIKCoZC29CW5bC0GdDIX8rbDyyY7jot2w+mm47G0weB7/HnHzlLwjFZmKW2zA8BNfA4T5D+Olmc9xqDKDZlszMd4JfJ27nHX564DWZ33G5wz3G+4yI2RV7iq+z/weUKSEP8/4nNH+o7ko7iKXtC8YvLg0JkSSpHjgaWAY0O7fIMvyoE3/uje/mhi/3k2SZqg9gremiSM1dmK8Ts0M2V68nZlhMxzK7Dp3aoNG4Jf2E0Vjr+52W+MDxvNp2qeUNJQQYBTqREOa+lIlH0crNUnnsrZwg1O1zKpMwjzCyKrJAuCXI79w0/Cb8NQrLz+93szwsCkcVwPGJ0r59BP5VZZ2A6SN8vpmCqstwghppbKhmV/2FzmVpxfVDn4jpLFG2bkIHg05m5zPl6Qq0tGZqxXj4kQYfSBqukNRXm0em4o2sanIsf3C+kJhhLiQ3blVTmU/7Svijjmx+Lj3o7tPXRFUHHYsk+2KUdLZCKk84nxt5q+KItuJDAqVShELOTrvSDfw947B31uZllU1VrE6d7VTne1F27ks/rIet300NruNZVnLnMp/zf1VGCEClwemvwM8DvwbmIMS2zGonYj35FUT6dvL+tnlh4nQe5FecWpGSKmllKqmSkK7SAxXFTmZ4F2fUjR6gSK/2g3cNG6MCxzH94e/56aRN510vwQDl8L6QsoayvDRuBMaMQ1y1gNgzNvGsOjhpFWkOdQP9QhlfcH69uMx/mNwb6iA8kNgDgdTAFTlQl2xkhehnyRJG1usZJc1YLPLRPoa8ei0k+nn7oZKAnunKDa9VoWPe8/cjKw2O9nlDTQ0WQnzMfTvpMfFeOg1jAz1ZM1BxzwE4a1GWl1jC0fKG1CrJKL8jNhlOFJejyxDpJ877roBIPdZX6bko9GZFLertueezghhEyF3M4SO78iFE3uG4gYTOl7JoC7boL68I8+CtUmZWFqbwTv6mJNEu2zHr4uYEB+9j3POHMEpERvg7HY1JtwTSVJULdWSRKSvEYNOQ0V9E3kVFoxuGqJ8jWjUvZihQO+l5DeKnw9GbyXuY+/nys5ZZ9z9lSzpwy4EJEXVqjQdNO6KK6BsA98E8Artta66a9xJ9kkmozLDoTzRJ5EKSwUF9QW4a92JMEWg7ubcoTNqlZqUoBR2le5yKB8bINS4BK43QgyyLK+UJEmSZfkI8IQkSWtRDJNBya7cSuYm9fIuQNlBQs2TSS23cU7Mybt97SjeSZxXnIMrVhuN3hHYtAY8c7ZQHTWl221OCZ7CZ+mfceOIGxU3HMGQYVPBJh5c+yAVjRWYdWb+NuthZv1QhKriMJpDK7hk5r2sL9hAcUMxAEneSfgZfKlvUfKI+up9+V3U+WhemQzWRvCKggv+A1/dphghBm+45HXlRdyHY6e4ppEXVxzkk605yDLMTvDnyYuGE+mr7GjG+Lvzf+cP48nvFBE+lQR/v3gkUb7d3/Gsa2zhw805vPBLOi02mcQgEy9dNYbEoKEReGzUafjj/ER251VTbVF8zs9ICmBMuDc55fU8/u1+fk0vRZLgqYtGsCWrgm93FwBw7oggHj4vmTDvfkx+VrQPlt4IZRmK29+8J2Hc9eDmofjkT75DccPyTwJzqCKnWn5QyVsDkHSeMkHc9g7M/T/FuF73Emx6WVnRjpgKF74Efo6y6k3WJn7I+oGMigyuSbqmXQpVo9LwQMoDJPsKuWlXMiHKh6mxvmw4XA6Ar7uORTNieODzPaxILUGS4IrxYVw/JZI/fr6H9KJatGqJP85PZOGkCIfFCZfiFa7Ednx3rxKYrnOHMx53Gi8EjVbG2voXldgO/0S44L/w65Ow/0vFdTBmjjIGw8b3Sle1Gi2XJVzGxsKNlDSUAMqzfrT/aG5YdgNZNVloVVruH38/l8VfhlHb89/1+THn83P2z+TW5gIQ7xXPrLBTyGMlGDK42ghplCRJBRyUJOkuIB8YtH487UHp03vZm6wik/CIMzhQbj+lZraXbGeU38hjnq+KnErg3i97ZITEe8fTYG3gQPkBhvu5JtGSoP/Jr8vnT2v+1C6pW9NcwwMbH+fzs54gOn8PqLWM2fwOr814nkN1uahVGuLdfDFte5ekxJtpwkZMQy2hOz9VfObLD0FVNvzyKEROU16glkplInjbGiXfRx+x8XA5H2/JaT9enVHKt7sKuPsMZQLgplVz9cQIxkd6U1LTRIiXnrgAU498yPfmV/PPnzp2idKLannu53T+e/U4DDrXJzXtD0aHe/HtndPILKvHqFMTH2jCx13H/349xK/ppQC46zTkV1raDRCAH/cVMSHahxunOavw9AlNtfDzw4oBAko+mp8fgpCxENn67AsaoeQHKcuAK96D7DWw+bWONtJ+gOn3w96lkPEThIyDjS91nM/ZANvehvl/c9hZPlh1kMc3KGtuC+IX8MyMZ6hrqSPaM5qRPsd+NgtOjhAvA/+9eiwZxXU0tthICPTg292FrEhVJtOyDJ9tyyPK150j5criSYtN5p8/pTE6zJMpsc47Vi6hrgR+eEAxQECJuVv2F4iYAp3jMuuKlPijNmqLlYD2tlxKoLhnhYztNSMElF2J1+e9zsGqg2hUGuI84/jbpr+1u9222Ft4duuzDPcdzrjAcT1uP9YrlrfPepvMqkwkSSLOKw5/4yB36xS4BFcbIfcBRuAe4ClgLvA7F9+jzzjSFpRu6EXJv8ZqsFqI8PXgyyMtJ91MbXMtuTU5XBBzwbHrhIzGP+0H9JVHaDyWXOBRqCQVU4Kn8OWhL4URMoQobSh1yunRZGuisDyd6DXPtZfFxZ9J3JhrlIMf/ww7P8JBQ8o7GkLHKUYIQPE+SDy743xzvfIi7ksjJLPMqeynfUXcMjMGg1aZMOq1akaFeZ30PXIrLE5lv2WUUlHfRKiuH3cAXEyknzuRnWLiGlts/LSvQxY01t+d/QXVTtct21fUf0ZIQwVkdaGVUpnVYYQAeEUoH7sdlj/qXL9orzJuD6+CwC6efWnfw8wHlJiQVvLq8tr//dnBz/js4GcAfH3R1+h1Qga6N/D1cGOKh+IK2Wy1sWxfoVOdnblVRPq4k15c216WW2FhSmwvdaquWFmU6Yxsh6ocRVGtjaPrRE3rOk4p81ew3OtowLiYOO844ryV53RebR5birc41cmryzspIwQgyD2IIPe+FSERDHxc6hQpy/JWWZbrgBrgHlmWL5VluYtf1OBgb341sf69G5ROxWEwhxDkoaa0Qaa+5ZjpVo7LnrK9RJmj0aqObVfKag1VEZMJ3P3FMet0xdTQqSzLWkazrfmk+iYYeHi7eWPQOAZhqyU1fvJRuwE+MZC/Awr3QsAwGiOmkD7/Mfac+ShVoxco2aTLOwVgekcpq3ntjWq7pV3vSkZ3YVxMjfVFr3Hd4y7Q0zn+Y1SoV+8uWAwA3DQqpnSSMs6ttHTplz8trh/ljvWeyrg8GoO3Es/RRkMl5G1TdkOiupCJ9kuA6hwIm6BkUw+fBLP/ArP+rMj2hk9V4k1aabG34Kf349ZRt3Jl4pXo1YrREeQehKfuxKpFglNHp1EztYvdjcRADwqrHRcOAs29GMNl8AH3LnZZTEHK8zJns2KQmI6SbC7Y5WiktBE6vmsDpKZQaas0XYk7cREmnYkRPiO4IuEKbht1G7ePup04rzgCDIPWsUUwQHGpESJJUookSXuBPcBeSZJ2S5LUe3uIvczu1tWTXqU8E0zBqFUS4SYV6RW2E1/TBTuKtxPtdeKVx6qoKfhk/obG4rx6eSz8DH6Em8L5NffXk+qbYOARYY7giZQH0UiK0aqSVDw07n6iD/zUUeni12DVU/DGHHh9OuUevjwfN4YrDr7HtYfe5w51FVlTboXCXUp9rVHxvT/wjXIsqeDMp8C7t5Ybu2ZGvD8pUd7txxE+BhZMCHdpTNOIEE8WpHQIQJgNGh49PxlTL0p5DwQkSWJBSjiRPooBW1HfTLi3geEhHbEwiYEenDeyGwnXeguDF5z7Arh1is8Zfins/BDWvgCWKig7BB9fCW+eAa9MUgwN307++oHDQeMGRj/FZ98rUjHIf3sGfntWmfRNugU0yv/vhpYGPkn9hEXLF7F4z2LW5K3hnnH34K5x56mpT+Fn7CW3H4ETl44PdVC0HBPuxZykAAeJnAUpYYwI7UXD0DMULnpVGUNtzH0UGsrh9Rnw9nx4fSZoDDD2+o46zfWKO2vwmI4y72gY0YVKVd52eHOu0tZr02H729Dc4Jruu3nyh5Q/sKFgA6/veZ03977J7PDZxHgOWqFTwQBFkuWTW3nvsjFJ2gPcKcvy2tbj6cArsix3YdqfPCkpKfK2bdtc2WSXXPHaBuYlB56S28YJWf20shoSOo7Fu5qYH63l6uSeqfQ021u4d9U93DJqEe6aE7uCBO75gga/OAomdN9TbmPBRvaV7WPx/MU96tsQoNsz174aly6h8gjWJdeRNfJCilTgj5qY9JXoznxKeVF6+EPq90oSLQCVmuXnPMEfDrzh0MzCmAv5k1sk6roSCJ8M61+CqKlgbwGVVvGtv+A/ykpeH1Je18ShkjpabHbiAjwI8nS99G5tYwsHi+uobWwhys+9PfC9j+iRReXqsVlUbeFQSR0atYr4AA/sssyhknpkWSYuwIMA8wBwPSrNgIPLoaUOjmxQJHcBblwG6T/Ahv8qx+5+MKI1IWFAMmgNirpRXTHYbdDSCL7R8PECx/YnLIJzngGVmh3FO/jdMsfn6QjfEfx9+t+J9ow+3UQ9+v2ZWVzdyKHSWlSSivhAD/w83DhSXk92WT0mvZb4QI/eXzCw2xWxg8ocZYxp9YqxYO+0Y+HuBzcth4YyRTraNxYOrVLq6D2UNkCR9j3j/zquayiHd86H0gOO97xlhWJQnyJ1zXXcseIOdpbudCh/56x3SAkakHmlu8Np9SMcLLg6JqS2zQABkGV5nSRJtce7YKBit8scKKzp1UzpgJJoqHWCFmZSsb+s5zsh6RVpBBgDumWAAFTGzCB8w2sUjVmAXdu9ydm4wHF8kvYJRfVFwq9zKFBbhKZoN/FFu3HQa2msgvh50NIAGZ203d39OWAp5mhWl+7gdorx3PM5XPQyZP+mfDpTnd/nRoivhxu+Hr0rmWvSaxkX6X3iikOQIE+Dk2HnbxoAhkdndEZY9VdFua0zjVWOY9s/GQp3KupEZelKDEhnIqfDqKMMEICDP8Och8HoQ0F9gdPpfeX7UEvq080AGRAEeuoJ9HQcj5G+fbxQoFIpalf+icrxweWOBggoMtKWCgif2FGW/VvHbnIbIWNh6t0dLln1Zc4GCCjy6C4wQqqaqpwMEKDLcS4QnAquNkK2SJL0OvAJIANXAqslSRoHIMvyDhffr9fILq/Hw03Tq5nSabEoDxN3xc8ywqzip6ye+3XuKNlJdA+2SZs9ArD4RuN/4EeKR3cvGZGb2o2JwRP56tBX/H7073vcR0E/0FwPZQeVSZhPjOK/XrRHGXOeIYpSS8QU5WUJcOB7xf3kyAYw+EL0rI4M6g3lJOidYzsmeiZhPLhVOdAYQaN3nPSpdYof9CkgyzJZZfWU1DYRaNYT5Wvsk4ldWW0T2eX16LVqYvzdMQ6E3Bf9RHldE1ll9agkCbVKccuK9fPAXT+A/yZ6TyXvR/Y6JTZpzELwCACtO8z5PyhNhez1SuxHyGhFzc1S6WyExM5WcuDMelDJO7JniSK7FDm9PSYk0BjodPt4r3g83UQsSG9TUd9EelEtlmYbcQEeRPTtjuTxqTyi5P4w+ipS0N5RSjwRshLDkfqtshtStA+aasA7RlFiO9oICZvgGBNi8FHctCqzHOuZj4oxOUnMbmaSvZNJrUx1KBdJiwWuxtVvkDGt/z06L8hUFKNkrovv12vsza8mxt854NKlVBxWHhqtk8AIs4qMChuyLHd7kiUjs6tkF5fHX96jW5fHzSV067uUDL8AWdM9968ZoTN4bfdr3Dry1pNKWiToQ+qK4denYfs7yvGUe5TkaqufVlbj/BKVINtv74bmOmVidsXb8MkCRc1KUsHl7yh5FErTwNbCWCvMDZ/DqtbYoHBTOAsj5qNd13qP7e/B2f+En/6syKKqtXD204oW/klit8ss21/EHz/bjaXFhlGn5t9XjmH+sMBeNUQyimq585MdHCyuA+CaieHcPy8B/4HgZtTHZBTXctfHO8ho/VucOzIIjUqFSiXxl7MTe8XVzSW4mRQJ3Y+ugKn3KL+FikzgGWVno6URRl6ulG97U7nmnGeVSWBB63pZyBhwD4SPLlGOA0coxsiuT2DqXe0xIYk+idw84mbe2vcWAGadmf+b/H946b369CufbmSW1fHiioN8s0tZoY8L8OC5y0cxNmIA7FBmr4MlCxXDVq2Fs5+B2Q/Dd3criS/dzHD527DjA1j3gmLYeobBpW8orq25rZo+fglKTFNnPPyVnedPrlaMF0mCmQ9CgGsULM06M49MfoQ7V93ZrqL4u2G/I9lH5LkRuBaXGiGyLM9xZXv9yZ68aiJ9ejtT+iEwdQRwmt0k3DQSeXUy4abuTbByanJQS2p8DD4nrtyJJs9QmjxD8T/wPSWjLj3xBUCkORJ3rTsbCjYwI2xGj+4n6GPytnUYIACho2HpzR3HCWcpibSalYklMbOUoNs2XXvZDl/cpPjPW5tBrSHIL4Gn1BpurM6k2dZMpGckgVozLFqtvGi9I8EUqgT1VucpwZlBY0B78m5RWWX13L9kF01WxTe6odnG/Ut28cPd04nupUWCFqudN9dlthsgAB9vyWV2YgDzh59erogtNjtvrctqN0AAftxbxP3z4nlx5UHmJvpz4Zjey+Z8yoSMhUW/KnlCKjI7yvd8phgcBTugoJPbyU9/hgUfgt4Mao1iqHzUabe4eB9Ez4Cbf3HY4TPrzNw2+jbOjDyTmuYawkxhhJvC++ALnt5sz65sN0AADpXU8d7GbJKCTRi0/bhLV1MEXy5SnouguPr9+EeY84higIBiPBTvg7XPd1xXnQer/gZxZyg7cLIMtUWQ/qOjvDRA1HS47Tdlt8Xgrbh9ddO9ujuMDhjNp+d9Sm5tLmadmWjP6JNKVCgQHA+X/kolSQoE/gGEyLJ8jiRJw4Apsiy/5cr79AV78qqYl+y8xe5SSjOcJPqizCoOlNkIN3VPuGxnyS5ivWJPKuKqLH4eYdveoyz5XOza7q3wzgidwafpnwojZKBTtM/xuL7c8VijU16CbQQOU150nbHbFEO5LU8IYAbGBIxxrBdy1HH4REcf51OgqKax3QBpo6HZRkldU68ZITWNLfyWUepUnlZUc9oZITWWFtZ08bcormnCy6hjV271wDZCQFmFzl7nXK7SKPLTR3PgK2WFGuCHPykTwc4cXqVMJo/CoDGIXEp9TGphjVPZ1qxKymubCPPpRyOkvqRjQacNWXaOT2qqw4ncTcrzs3MSw5CxSl23o555PjHKp5cIM4URZgo7cUWB4CRxqUQv8C7wM9C2vJ+BksBwUNGWKT3Kr5d9S8sPKtuvnQg3SaSWdz84fWfJDmK9Tu4h1OQVhsU7goB9X3f7msnBk9lZvJPCOueEUIIBROAwx2PjUXkbbC2Ku0obpemOspBtePbwBWS3K8Z15m9Km/aeCy1UW5rYdLiMn/YVYtCqcTsqv4dBq8b/qKDzkppGNmeVszOnktpG56SfVfVNbGxtM63IeeLSGbNey7Q4Z0nVhEBTF7WHNma9luld/C0CzG5UW1qIC3CnsMpCflUDv6aVsDK1mNyK+n7o6XHQeynxG0dja3E2oAFCO6n/hHcR5Bs9SxFuEPQ7SUFmp7JxEV74mpx3X/fnV/P9ngLWZJRSUuOcbNSleAQ45wABJWauM25dzDFCJ0DJUUHnEVOdDRBQVLMyf1MSa7Y0Op8XCAY4rjZC/GRZ/gywA8iybAVOLvFFP5JT0YBRp+7doPTmeiVA2MNxtyXCU8XeUvsxLnKkorGCMks5oR4nvxJZlnAWQbs+Q93VikwXuGncmBIyhU/TPj3pewr6gLCJDjsYFOxSfNnbYnnSfoLz/qXk9gA4tFJR+vFoDTyUJJjxRwjqgbq23a4EWr4+A96/UJGj3P9ljwyRkmoLL608zNVvbub3H+7g0a/28NeLhrcbInqtihcWjCa60wJBRnEtVy3eyJWvb+KSVzbw8Jd7KeqUmKygqoF/rzjINa1tXvvGZjYccs6q3oZWo+K2mbFE+3W4Hlw+PpRxA8HPvI/RalRcNTGCSN+Ov8WZwwI5Ut7AjDg/dudV88AXe/hmZwE3vruVm9/bxh0f7WBvflX/dfpotHol/skrsqNs+KWtK86TILBTYsOYORAzu+M4chokX9hx7J+oBBK/fQ6UOAbtCvqeYcEmzhnRsTsZ5Wtk4eRIJ1esDYfKuOHdrdz18U6uf3sL/15+kMzS7r3zTgpTEFzyekeuGpVGkXP2iVd25gB07hCSoqhetcW3mYLgjMcck2oGjlRil47myEZYPFt51r4+Eza+DE2DUoxUcBrj6v3KekmSfFGC0JEkaTLQ/ax4A4R9BdUOk5xeofyg4jOvcrQDo8wqlqY5r+R2xe7SPcR4RaOWTj5IvNkUQH3QMIJ3fEzelFu7dc2c8Dk8s/UZbh9zu1PWbcEAwRSo+LxPWARWC/jEKko+MXOgvhR8opUg25BxituAKRB84+CWX5XVNb0Z/OJ75mNckQlf397hcmBrhm/uVAyZNpnKE7Anv5q31nUovhwoquO73QV88fsp1FisBHnqifJ1bw9Kt9rsvLs+m8yyjpXp7/YUctbwIM4frfR9b14N72080n6+vL6Zp39K5c3fpRBo7vr7JQaZWHLrFLJa1bHiBroSVC/RYrWzZGsO02L9uGiMjigfdww6FRnFdVRbWliyNReAUaGeGHVqGppt7M2v4ed9xYwM9erfzncmaATc9LMyRlUa5bkrqZQEhVEzFINCrVXyhJg7JVr0DIOL/gejr4LC3cpvZfU/lZipja/A+f/qmFQK+pwDRbVE+Bh48coxNNvsWG0yn245wqhQTwxuyu+1qKqB55enU1rb1H7dJ1tzmRbn17viMzGz4LY1UJ2rqA76xivGRsBaqCtVFAp9YhUFt5FXQGMt+EQpY84nBkr2Kws4/klKvF1n6svg27s6Yk5ku5JYNmoGREzqve8kELgYV79V/wB8C8RKkrQe8Ad6Jts0ANibV02Eby8HYJVldOnqEuguUdUkU90k4+l2/EiP7cXbifU69WzUZfHziFrzH4pHXkKLh7MMq3MfA4n1jOW7w9+xILEL/XzBwMDNBKHjHMuODm70i1M+bXiFKZ+Toa5YkZ3ujLVJKe+mEVJQ5exSsO5QOSAxtQu3oNomK2sPOccs7C+o5vzRymSysNq5zb35NVTUNx/TCAEIMOsHRtK9fqSmsYW1B8va/4azE/0prW1if4GjS1tmWT3BngYOt64ub8mu6PO+nhBzcNcSpnqz8yTv6PP525Vs653JWq2sPBt7JgoicB1phTW8vT7boSzUy0B5fRNhrUZIWX0Lu3Od10KLa/rAfcknWvl0JiBZ+bShM0LwUQqCxxqrbTSUK/F6R1OTf/J9FQj6AVcbIbHAOUA4cBkwqRfu0evsza9mWqzzhMellKR2GVCmkiSiPJWkhVNDj/2na7Q1cajqEPMi551yV6wGL6oiJhK69V2y5zzQrWvmRc7jnX3vcFn8ZUKuV6BgClJcDJo7xQRoDeDR/WDuMG9no2BYsBk/U9cy0ma9lnlJgdhkGS+jFrUkcaCwlpFhXu11Qr2cDYmx4V5OcSUCZ8wGLbMS/Pm0dccjo6iWuUkBjA7zwt/khiRBZmk94T5GfkvvMAYnx/geq8nBSVfxUrHzOtxtBP1CcrCZM4cFMiLEjE2WqbFYqWtqcYgJ8ffQMT7Ciy3ZlQ7XDlhp6e5g9OuQT+9MT2P4BIJ+xtUxIf8ny3IN4A3MAxYDr7r4Hr2KLMukFtb0clC6rATtenW9+hZpVrHvBJnT95XtJdQjFL3aNROpitjZeGdvQF955MSVgQTvBAwaAytyVrjk/oIhgE+MonGva3Vx0BrhksWKm1c3GRXmxZ1zYlGrlF3AAJMbj56XTNAxdizUKokLxgSzKq2El1Ye4t8rDmJptpIQ2OFmMTrMk9tmxtDaJEFmPQ+ek4TfQMvwPQDRqlXcPD2apCAlKL+gupF5wwLZmFnOiysP8p8VBymosjAs2ISlRXlmTYjy5qxhvaws2NeET4Jxv+s4DhwOk29XZHwF/caIEDMtVjv/XnGQl1Ye4pf9RSxICXeICQn0NPCH+YmEeinPEJUEN06LYkToIDYg3X3hwv+Ce6vngkoD8/+ujEuBYBDh6ido28z5POA1WZa/kSTpCRffo1cprmlClsHb2It+vnXFgKxk9O2CSE8Vu0uOb4TsKD55VayusOuMVMTMJHTz2xw++8kT1pckiXOiz+HV3a9yZuSZqCRX27OCQYckQeK5ih90XbES5O4T2xF02Q38TG7cOTuW2YkBVDe0EOlnJD7g2KpULTY7S7bkklfZ4Qa25mAZ+wtqiGu9LsDTwN1z4piXHEBNo5UoPyOx/qef0tXJEh9o4qNbJpFdXo9Jp+GLnflklXXsdm07UsnFY0P4+JZJWO12EgJNg3uVuStMgUrizQk3KzFPPrFKgLqgX8ksq2d1JwnpgupGPt2ay9hwb7SdVPUmx/jy1u9SOFJej9mgJTnIhJf7IN8JDZ8It66Gqhwlm7pvvIhPEgw6XG2E5EuS9DrKLsgzkiS54frdll5lf2tQem9mY6Y4Fbyjjzk5i/ZU8VPmsYPTbbKNPWV7uH7Y745Z52SojJpGzK/PYCw7SINf/Anrj/YfzXeZ37EqZ5VL3MIEQwBJAt9Y5XOSGN20TIjqnp99fZOVjZnO8QdphTVc1Cl/hYdBy4ToIeYi1If4erjh6+FGY4uN9YedlcV25VazcHJU33esL9G5O/vuC/qV9CJnNajNmRXUNrXgo3E0MpKCzSQFD+Ldj67wDBMuWIJBjasNhAUoeULOlmW5CvABuhdkMEDYX1BDuE8vr+IV7wXPY2fTDfWQKGmQqWmSuzx/sPIgnjpPzDrXrubKGh0VcXMI3fLOiSuj7IZcFHsRL+54Eavd6tK+CAYINQVw+FfIalV06QPqGq3szKlkdXoJWaV1NFttHCioYVVaMamFNTR3Sl5o0muZlxzg1MbocK8e3VOWZQ6V1PJrWgm7c6toaBLjuSuqGpqZneD8954aOwgNvOo8JfFg9npFbUgw4KlvsrIrt5Jf00o4XFLHiFBnb4IzkgJ6V16/v6jKVaTUszcogekCwRDApTshsiw3AF92Oi4EBlVWu3351b2flKxor6JTfwzUKomo1riQroLTtxdvJ8YFqlhdURUxqUe7ISP9RvJz9s98dfArrki8olf6JOgnSlLh4yuhqjVOKGwSXLpYkZHsJaoamvnPioO8uyEbAKNOzQsLRvOHJbuwtNhRqySeuWwUl4wNRa2SUKskrp0cya7cKnbkVCFJcN2kSMZH9iynx9qDZSx6f1t7dva75sRx+6wYPIbiZOYkSSus4ab3tvLoucOYEOnN1iNKoO/Zw4OIC+hFqdPeoHg/fLQAavKU46iZcPH/wCuif/slOCY1lhZeWX2I137LBJScQW//bgJXjA9j6Y48ZBmGh5i5YHQwGvWgcsA4MUV74aPLobZIOY47Ey74j9gFEQx6htgv9dRJLaxxSMzlciyVyqerbKqdiPZSsbvUOS5ERmZHyQ4SvE9sIJwMslpLRcxMgrd/1K36kiRxRcIVvLzrZWqbRaKkIYMsw/b3OwwQgLzNkPlrr972QGFNuwEC0NBs49ll6ZwzUvm92Owyj3y11yEmIdbfg7dvmMDXd07jx3um8/B5Sfj3IOi8pKaRB5bubjdAAF7+9RBpXbh6nK5YbXbe3ZCNTq1iZVoxPh5u3HtGPPfNi6e6sYUNhwfRyqzNCpte6zBAALLXKDsiggFLWlFtuwEC0Nhi589L9xDhY+CeufHcc0Ycsf4evLU+a2jtZFqbYd2LHQYIwKHlkLOp//okELgIIe3RibomKyW1TQT3ZlBl0R7FX151fPsvxlPFjiJnI+RITQ4g4Wc4cT6Pk6UqYhKxq/6JW3U+TZ4nzsYe5RnFKP9RvLjjRR6d/Giv9UvQh1gtcGSdc3n+dki5sdduW1zT5FSWVVbPeaM6jPYmq53y+ibi6Fh99zLqGGPsWsb3RFQ1tHR535Ja57LTFUuzja3ZFUT5uZNeXMu+/Bp+3t8xKfJ1P7m/fb/QXA+5G53Li/YCV/d5dwTdo6TWOa9HXpWFJpvMy6s6cmaEehmoqG/C6DZEpjfNdcoC0NEcLc8rEAxChsiv1DWkF9UQ4WNslwftFfJ3glfUCavFeatY0kXm9O3F24n3jqcXe4iscaMqcjJBuz/nyMz7unXNpXGX8vjGxzkv5jzGBoztxd4JXIa1WZGKrs5VduYCkjoypGuNkHyhYjR3JnqWy7tRWttIRnEdLTY7gSY3Zif4My7SmxabHZUksTOngoxOuxJmvYago5II5lY0cKikDjeNioQgE+W1TWSU1GG12YkL8HDIG3I0fiY3EgI9yCiucygP7yJnyemKh17D2cOD+Hx7HueNCmZStC9mvYZYf3cqLS0YdRq2ZpdjaVb+3lq11P7/NC7AgzBvF+0uW5uVyVd1nvOY7S56szK2j04+KDJND2jCuxhDw4JNJAeZeP6KUTRb7ZjctOzKqcRqh+9256OSVCQFm4j192BPbhWHSuswG7QMCzbjb3LjUEkdeZUNBJj0xAd6YNT18pSouUEZv7VFiuufXwJoTmDA6z0h6XzY9Ipjeci4rusLBIMIYYR0IrWwlnCf3syULkPBThh33QlrBhglWuwyBXV2Qjw6dk22F2/njIi5vdhHhcrIKUT/9jx5k27G5nbiGBkPnQfXJl3LQ2sf4osLv8Bd25t5VgSnjN0O+5bCN3eC3OqGdNbTkHIzaFtVZUZeAfnbIGOZono17kaInuHSbuRW1HPPJ7vYmVsFwJ2zY/Dx0PGv5RkAuGlUvHzNWJ78dj+grLg/dsEwgjolI9tfUM31b22hvL4ZgFcXjuOlFQdJbTVcgsx6XrxqDJOOkUDPx13Hc5eP5s6Pd5BXacGoU/PXi4b3fmzYIEKSJOYkBbD1SCXjIrz5+w+pXD0pgn8uS2+XR47xc+fcUcHsOFLJr+ml7M6rAsDf5Mb7N00k+VSVidrH7B2KuyDA2f+E8Td1jNnufRkYc62yIJS5CiQVTLwdIqacWv8EvUpSkIlnLhvFE9/ux9JiI8LHwFMXD+fvP6SxI6cKUH7LL189lmve2ERBtbJzMirEzP3zE7nr4x3UNyveBWcOC+SqCeEsen8b9tah9ODZidw4LQq9tpemRS0W2LIYVjyuHEsqJcZuxOXHlzFXqZXncuEeZXdapYbJdyoSvQLBIEcYIZ3YX1Ddu6ufVbkg2zoSDB0HSZJI8Fazo9jWboQU1hdS11JHsEdI7/WxFZveTH1AMn5pyyge3b2A83GB49hbtpfH1z/Oc7Oe612ZY8GpUXEYvr+/wwAB+OURxcgIGqkc+0TBpW9CZZby4vOJBa1rE/xtOFzRboAA6HUavtzR4ffdZLXztx9SufuMeHIrLdQ3Wfnb96mEexsZF+lNs9XG4jWZ7QZIoNmNwyV17QYIQFFNI1/syGNsmBc6nbrLfowO9+LLO6ZSWNWIp0FLpK9RjN9ONLVYeW9DNvOT/dmUWY5aJVFYZXHIz5JZVk99oxVfD127AQJQWtvEuxuy+PvFI08tYLh9zHZSDfz5YYiaAUEjetaWbywseE8Z22qtMrY1gzxvxBDHTatmQUoYE6O9qbFYCfEy8NPewnYDBKCivpm31mUxI8GfJVtzAThrZBDP/ZzeboAALD9QzOgwz3YDBODZn9OZHufPyLCu83edMqXpsPKJjmPZDt/dByHjwfcEOb/84uCqj5XxqnFrHa+DyAVSIDgGIjC9E6kFtUT05k5I7lbwT+p28rZYbxVbCzsC7LYXbyfBOx5VrzpjdVAVOYWAfd84TlRPwNVJV5Nemc7b+97uxZ4JTpmGCiXpWmdku7NUqd4EwaOUTLwuNkBAUVzqTGOL81g7Ut5AbqWFl1cd4p312ZTWNVFWp8RrNDTb2NlpEpIUaHJyqwJFeru2+fjBqgEmPaPDvYjq7TxBg5Aai5UDhTV46BUDI8zbwOFS579zVll9l/8Ptx+pas+oftI0lB9jzJ6kdLTerOT9CBgmDJBBgiRJRPt5MDrcC3+TG9nl9U510opqSQzsiBeL8DGSUewsMtFodRynsgzldb0YB1Zf6mhAgxLvYXHOc9QlBk8IGQMBycIAEQwZBsxOiCRJ2UAtStZ1qyzLKX15f7tdJqOklgifuN67Sc6GHvkdJ/qoWJLaEReytWgrU0Om9UbPusTiHYms0mDK30VtWPf8T3VqHXeNvYunNz9NgDGAC2Iv6OVenia0NEFpqpId1xSkTJzcTiCLWlsMJfsVNwC/RGU1rQ1ziJLxubPRoTUeN39Nd7C0WMkoqqOgykKwp4HEIA8MR/lZHymv52BJHVq1innDAmi22fE3uWGXZZKDzBi0aocJ671z4kgKMfPkhcPxcdeyJqMUPw83ft5XiL/JjXNGBPH6GmX3ZOuRCv58dhLf7i5wuOfsBH98PcREs6dkltZxpKweo5uGO2bHYtJr+d2UKIprGgk269l2pNJhXjUyzBOD1nlt67yRwZhOVe7YHApGX8ccCTp3ZczarMrvoyJLGdcBw6C2EMoPgd5LOXYfhLlMBMdlRIgnC1LCCfXSY5NlbHZoaGpBq5K494x4JAmaW+xMj/NzyKwOYDoqcN1NoyLES8/W7ArK6pqI9DESH2hCe7K7d80WKNgBFZngEQgeAYqxa+1k6JiClGexQHCaMmCMkFbmyLLcL1mj8iotuOs0eOh76U9iqVTkTsdc2+1LYjxVZNfYqW2WabSVUd5YTripD3XBJYnq8AkE7P+u20YIgI/eh/vG38dzW58DEIbIqSLLsP8LR1/42Q/D1LtBd4ydu6oc+PJWyGlVAdJ7wnVfQ2jr/0evcFjwPnyxCGryFRfBi187pUznLTY7n2/L47Fv9reXPXpeMtdPiUSnUdyg9hdUc91bW6hodZ968OxEduRUklqorFR6G7X856ox/GHJLuqbbVw/ORKVWuL3H+5ob/PBsxJ5Z+1hvttXDMBzl49ibpI/q9JKabHJhHjquWZiOEu25WGzy8xLDmD+8MCT/l6nKztzKrnurS3cf2Y8L648yN1z4/nbD6lUNigLI8OCzfz1wuE89u1+JOD8UcFMj/NjT14Vt86I5u312VjtMmcNC+TScSdW2TshXuGw4AP48hYliaa7P1zSOmbTf4LPFoK91Xgdf4NihGf8pBwPvwTOeQ48ek9VUND3RPu58+7GbD7bprhemQ0aXr12PPct2UVpq7pdtJ+RZy4bRVl9E/vya9BrVdw2M5ZJ0T6EehnIr7Lg467jpavHsHR7PovXKgsaKgn+e/U4B2W+HrH/S/j2rg5Pgqn3wmXvwHd3K4a0Zzhc9qYwQgSnNQPNCOk3Uot6OT/IkfXKNqq6+39yrVoizlvFtiIrFts24r0TUEl960FXEzqW2FX/RN1YjU3ffV/ZUI9Q/pDyB/61/V8UNxRz84ibhYvLyVKRCT/80XErf/U/IGE+hBxDiSx3S4cBAtBYDb89B1e80+FWFTkNFq2CumJlhfkUE19ll9Xz1PcHHMqe/imN6fF+JAWZabHZeWd9drsBYtSpqW20thsgAJUNLXyzM58/nJlAlaWF0WFe3Pbhdoc2/7Uig38tGNNuhDywdA9f3TGFB85KQqdWEeFrZEqMLxePDcNmtxMf4IFfD/KGCKC+2cpzP6czLMTM6vRSInyMbM2qaDdAQMnpUlHfzP3z4mmxyaw7WMZvGaXce0Y8KkliwYQIrHY74T5G3F2lOhTVNmZLwOgHnqGKQfLdPR0GCMD2d2HOIx1GyP6vYOx1EHeGa/ohGBDsya9iT151+3GNxcpb6zKJ9DG2GyFZZQ38mlZCUpCJuUkBWG0yX+3MZ3S4F1/dMZWS2iZ83HUUVlvaDRAAuwwPf7WX0eGePVd3Kz6gxNh1dmXe8CIs/AZu/U1xwfIIApNYHBGc3gwkI0QGfpEkSQZel2V5ceeTkiTdCtwKEBHh+qy2aYU1hPZmUPrhlRA+uceXJXqr2ZBvxcoWJgb1vRqGXWekLjAZ34yVlIw6dpb3rgj1COUvE//C/3b9jwPlB/jr1L/ioRtkmZVPQG+PS0DZRWtpcC4/On6jMxVZzmVFu6Gp1jG2wxSkfFxARUMzLTZHn2ebXW43OhpbbOzqFITu466joMpZ+z+jpA6bDD/vL+Kfl47EZndss8UmY2l2jC/Iq2zkgtEdK4pag46J0T6n+pUGNacyNusbraQW1jAnKYBNh8sZHe7VpV/9kYoGNmdWkF+lBKh7GbW4aZVdr17Lom4Kdkz22ljddVyI7Sj//rri3umPoEe48pl5pNz5uZhRXMeEKB+2HalsLztcWs+R8gaWbs9vLyurbSLArCegVe57X361U1vVlhaqLS2EefewY5YK5bl9NLV5EDdb2dUTCAQDKjB9mizL44BzgDslSZrZ+aQsy4tlWU6RZTnF39/1W+r7C2p6Lyi9tgBqChVN8B4y3E/Fb7lNlFpKiTRH9kLnTkx12Hj805ed1LU+eh/+MuEv2Ow2Lvv2MnaW7HRx7/qX3h6XgLLaaz7KnUWjB6/jjIfQLnZIhl+iqKvs+woKdtPYVMee0j0sy1rGzpKd1DU7Bxr3hBBPA95GR7//mXG+yDJ8tOkIazNKuW1WdPu5wupGYvydpZynxPiyu9VY0WvVmI9ykfQ2atFqOnbVJAmienMXc5ByKmPT213HuSMVud1pcX7syq1iShcSx1G+7hRWdyhkzUzoB3cnUzAEj3Esk1SgPioGyPfU4v2K64tZm7eWFUdWkFXdhZEv6BanMi6zSur4YU8BH246wrqDpYwO93KqMzcpgB05jgZASpQ3WWWOQezRfo7PnghfI5qjcoTF+rs75STqFp4R4BfvWKbSnPIYPBkqLZVsKtjEz9k/k1aehs1+igIRAoELGTBGiCzLBa3/LQG+Avp02T+1sBeNkIzliqqFqmt50OMR560iu0Ym3DSiz12x2mjwi0PbUIm+IvukrteqtSwctpDLEi7j3lX38u9t/6bF5pyIUXAMTMFK/IZPa7yGKUiRazz6JdeZsAlw5l8VYwUg8TwlOPetM2HpDVi/vIWvMj7j2h+v5YE1D3D9T9fzwYEPaDxafagHBJn1/OOSkYS17iiOCjVzxYQIfvf2Fh75eh93fLyTn/eV8NA5iUgSqCWJIE837jkjDp1ahSTBhaNDmJngT0OrktWPewt4YcFoQjyV7xHmbeCFK0bzwx4l8NzToOWlq8aSGCRyergSrVrFLTOiifFzx9/kRnyAB25aNWckByBJShDvLTOiUbe6WGpUEldPDGfyMXKx9CoGL5j3hDK+AYw+cOF/FZcYADczXPRKh/T0SZBXm8ddq+7ijpV3cP/q+7n6h6vZW7r3lLsu6D5ZJXU880s6d368k0e/3sf1b2/Bw03DXXNicdMo78a5if5cNCaEyTE+qCTFpfn2WTHMjPdnXIQXAB5uGp6+dCTDQx3z1sQHmHh14Xh83RXlqYRAD/5z5diTE7TwjoBzngf/ROXY3Q8ufFkRCOlDKhor+Pvmv7No+SL+9NufuOqHq9hQsKFP+yAQHA9JPloyrj86IUnugEqW5drWfy8H/irLcpfL7ykpKfK2bdtcdv/6JivjnlrOW7+b4Pps6bYWWHoDjL9RUcc4Ce5ZeZBL4uu5NKH/XJn8Un+kxd2PvCm3nlI7NU01vHfgPRqtjbww+wXCTQN+W7rbA8LV49KJ+jKoKwKDL5i7ESxpt0NlNtiaoaUe3uhIcpl5xkNcnv0ZLfYOY1BCYsn/s3fWcXJV5x9+7rjPrLtlsxLbeAIJIRDc2uLFirSlWIXqr+5CgRYpLVooDi3Q0haKEzTunuxm3XV23O7vj7uZ3clMZH03Oc+H+ZA5c+6Zd2bvnHvfc973+57/AtNSpg3JvN3NTi75y6ecW5FFqkXPspJUvvXi5miozgEeuHIupZlWNJJEfoqyGlnb4SYky+QlGTFoNexqctLrD5KfbCLDZmR/m4s2lxI+UZhipscboKnHh1WvHd0wyonLoCaqoZ6b7kCIhi4vOrXEhtpuMq06Wl0B9rS4eGN7Cxa9mmWlaUzLtHJySRpW4zAVsIZCTwM8cioUngTJReB3wbaX4YrnFOEGrRmShreL/K/Kf/Gjj34U03Zq3qncefKd6IW878GMypz52tYmbnlmQ0xbmlXPY1+Yhy8kEwrLBENhnl5dxx8vn02z049KgrxkE1q1CpcvSEO3D5NOfdiixI3dXpzeIBk2A0nmIUrhdtfCX8+GE29TBBQiQfjwLvjsA2NaFPOTxk/4yltfiWnLNGfy3LnPkWpKHTM7JggiKXUCMlFyQjKAV/oSlzXAs4dyQEaD3S1KpfQRd0BASUg3pw3ZAen0dmLW1lHdMwuIj1kdK5w5c8ld+wT1J3xJCXUYIja9jdvm3MZbNW9x5X+v5K7ld7E46+hli49rzKnK42hRqfqLYO34V8xLTpUqxgEBkJHp9ncP2bxub5BefyhaJOyEKclxDghAuyvAeemxOxdFabEOdvlB1bWL0iwxfexGHXaj0Mofbcw6DaUZVnq9QR54r5IvLyvimdW1bB0QP7+5vocLZmdzXsU4qfz4nUq+x7aXYtt7GmDGZ0fkLeqcdXFte7r24A15hRMyRhzILRtIW6+fLk+Yax9fE23LTTISCMtxOUkWg5ayzCM7ydkOI9mOYS5s+HoU1cE3vh/b7u5I3H+U6PLF56U0u5vxhBLkGAoE48CEcEJkWa4CZo/X+49eKJasXBgLThryCDs6d1KeEmFdkwFZ7jnaOocjTsCWRVhrxNq0ld7s4f2pJEnizMIzybPm8e2V3+aHJ/yQswvPHiFLBQlJnqKEA/bFA2e5Okg3pdPqaY12MWvN5FqGrpCV6zDxxZMKmZVjp90VwBcIc92SAp74pCbaR5KgMPXwv7WadhdbG5x0e4MUp5mZl+dAP1LqSoIhYTVquXZJAakWHZfOz+W0aen0+kI88Uk14YjM0uIUtjf0MCNHUdCr7/Kws8lJICRTlmlhavoohstZsyFnATQMWFFXqY9chXoQzEmbE9d2/pTzsetHqbq2II7CFBMqiZgq53PzHaRYtPz+kgoCoQh5yUZaur10ewKsrupAJUlMy7aNbhHiRNhyIH2GUqfpAGqtMg+PIQW2AiQkZPq/tCXZS0g1Hne7IIIJiriyA9sbnNE49hGlcZOiapQ+1DhQmR0d21mQvpA1jVDXqyHfdviqz6NJb/ZsUva8NWwn5ADTUqZx+/zb+c2q3yAhcVbhWSMyriABadPg8mfg318HVwsZTTv445m/4adrf8e+7n3kWnL5xdJfkGcbenhckkmDQavmGy9sjrbdemoxl83P5cX19SSbdXznzDJK0g4dVljT7uKH/9zGR/uUFUOVBPdcPofPzBmBOhOCYVGcZubGJ9fj7lMmy082ccvyYnyhMK1OP9e9tZYHr55HkknHDU+spbpPucii1/DslxdTkesYHcOMdvjMvfDv26F+jVIY7vx7lHN+hKhIr+C7C77L/Zvuxx/2c17ReVw49UIhOz6GlKSbuePiCn7/v920ufzMzXPwf2eX860XN7G7RUk6N2rVPPKF+Vz450/o8So7vdl2A09+cdHoOsIHY0qGix6CV7+mFCy0ZcMF90Ja+djZAJQllXHX8rv49epf0+nrZFHmIr678LuYtELIQzAxEE4IsKPRyQWzh1iQ6HBsfg4Klw05fKnZ1UI4EibVlEJpcoC1zfpxdUKcOXMp/OAeapZ9DVk9MqEwedY8vj7v6/zy01+SYkhhQeaCERlXcBBqDZSdo6gI+Z1gzaLCYOPxsx6n09eJQ+8g2Tg8SdvtTU4eXFkV0/bn9yu59/I5LCtNwx8K8+f3K8l2GMg+hO7+1gZn1AEBZdXzN6/toiLXTmHqsSXvPJnw+kP89aPqqAMCUNvpwWrUsnt/D2/uVCRy39zeQkmGJeqAALj8IR79cD93XzobrWaUxDUyZsLVLylV0vW2o8uZGgQ2nY2rp1/NioIVBMNBssxZIgxrjNnX5uG+d/bynbNKMeo01HZ62FbfE3VAQAnF+sf6+qgDAtDY4+Ptna1j64SAIoRwzT+VPD69HWwjI4U+GLRqLWcWnsnstNm4g24yzBmYtfGKhALBeHHcOyGRiMye1l7yR1o6r3mLEqc8+8ohD7G1Yxv5NkVHvSwpyKpGAxeXuo9w1OgRMjrw27Kw166lu2jpiI2bb8vni7O+yLdWfovnz3ueLMsoOIQCBVsW0P/9OgwOHAbHiAzd4wnF1fSQZdjb6uL+d/dF27o9h1ZG60rwWrPTh8svZCXHE1cgRE1nfBz57mYn25v6pZ33tbpITaAmtKvZiT8UHj0nBMBgUx6jhCRJ5FjEjtx40e0JUNfl5bsvKapkU9LMnFoWK/GbaTckrB2yuzm+xs2YYLQrj3EmwyyKIgomJhNGone8qOn0YNFrsOhH0h+TYf2TMOVUJTl4CITlMDs7dlJkV+oqFCcF2NulxR0c3+3/3qwKUva8PeLjzkydyWn5p/HN978ZlzAtmBwUpJhIs8begCaZtHiD/Q6ESoJUi45nV9fw93V1bD+oQFhxupmD9SFOLk0j7/hUwJoQyLJMry/EOTPiV3KLUi00DqgTcvr0DErS41daL5mfi8UwDspZgmOGolRzjHhMVZubWTmOmD6b67o5fVq8CMxZCc5dgUAw/hz3Tsj2xp64okXDpmGDUjH14AJag2B/dxU2nQWLVglB0auh0BZiY8v4hgA4syuw169DFRh5dY2zCs9CJal4ePPDIz62YPQpybByz+VzKMtQwh5K0i3c9/m5NPdVRc+w6fnj5XP41Ws7+cEr2/jOP7bw5SfXRQsTAszNc/CHy2aT3ufMLCtJ5VtnlGI3CSWs8WJdTRfn3Psh2Q4Dly3IRaOSsOo1fP+ccrRqCZ1ahUGr4rolBczIsjK3IImfnD8di16DVi1x3ZJCzh8v5SzBMUNZpo1HvjCfrL6aQSeXpFKUauJrp03FZtCgVkksL01j8ZRkvrJ8Cjq1CpNOzf+dXc7iouGFmgoEgtHhuA/H2tbQc1jN8MEjw/onYOppQ94FAdjctoUCW1FMW2lygE8bDJyUO/SCcsMlojPjSSkmaf9HdJSdOaJjqyQV1864ll98+gtW5K8Ycr0KwfixdGoqj1+/gA5XgBSLjmyHiQWFyXzrrDL0aonfvr6LnU39oRGNPT4+2tdf+dio0/C5ublU5Dpw+8PkJxuFAzKOeANh7n17D/5QhO+/so3zZmVyz+VzyHIY+GBPO//Z0sQNS4uIyDL/296Mzajlm2eUccNJRZw1I4NQRCbbYUSrPu7XuwTDRK2SWFGewb9us+P2h0m36XlhTR0vrK3j0gV56DUqPtzbzl1v7uGhq+dz1aJ8VCqJHIdRCAgIBBOU494J2Vrfw4nFIyhXV/OJUhwuY8aQh3AH3dT11jEnfW5M+7TkAH/ZZCciExeyMpY4+1SyRtoJAUgyJHFx6cX8+OMf88L5L6AeQpV5wfiS7TCR7eh37I06NUWpZtp7fexuiY/Nru+MryUy5TAKWoKxwxsMxySZ/3drM//d2sydF89i9f4OKttc/GVlf07I3pb+f+ccQnxAIBgO6VYD9OWYN/X4aHH6eeyj/dHXc5OMuPzhaCFUgUAwcTmunRBZltne6OTKxcOrpts/YBg2PKnsggyjoN/Wtq3kWnPRqmL/PMnGCGatzO5OLdNSxi9vwpUxg4ytr6B1dxA0p4z4+Euzl7KqaRXP73qeq6ZfNeLjC8YOfzDM9kYnlW0u0qx6Pr8wH5dfSWCXJAiEIszIjk0mburxsrW+hx5vkOI0CzOybei1/c6or2/MqjYXSWYds7LtZPSFaAiGTiCkfK/7Wl3YjVpm5tjJdhi5bEEef3hrD+UZVr52+lSanX5CMnzppCI21HQTCEeiY4yKyqBAcAgWFjhQSVMw6dSEZRmdWo1KkvEFQ/xzYz0qlYqZ2TaxqCEQTFCOayekoduLWiWRbB6hcI+qD5SCRKlDrQuiVK3e2LqJEw5RRbw8OcCqRsO4OiGyRocraybJ+96lZfalIz6+JElcWX4ld669k7OKzhKFlSYxb+9s4dZnN0af//mqedz+wib8IeXGNd2q59yZ/bLMLU4ft7+wiVVVndG2B66cG1ON+3/bmvnGC5uiz5eVpPKHy+bEJcULBsf7u9v4ytPrkfsEzublO3jgqnlcPC+XHm+AhYXJfP35/r9dhk3P3ZfN5nsvbUElSXzttBJOnCJ+q4KxI8Wq579bm6jvUnZTdWoVD14zjwv//DFOnyKIkWzW8dyXF1OWOXrKaQKBYGgc14G6W+t7KE4boS3bSBg2PgXFpzOcsub7u/ejVWtIMSbeYShPUfJCxhtnzjxSd70xauNnW7I5MftE7ll/z6i9h2B0aXH6+NmrO6LP5xck8cLauuhNLEBrr5+1NV3R5zsae2IcEICfvbqDFqeSB9XU7eVn/94e8/qHe9vZ2eQcjY9w3NDe6+dnr26POiAAG2q72d7oJCfJyO2nl/Lcmti/XYvTT3W7mxuXTeGuS2dz48lTSBqpBR2B4ChYX9MVdUAAAuEID66s5PKF+dG2TneAt3a0jId5AoHgCBzXTsjGum4KRkoZq/IdpUhWypRhDbO2ZR0ljkPXLMm3hejyq2h2j2+uhCdlChq/E2P7viN3HiLnTzmfD+o/YHvH9iN3Fkw4fMEw7W5/9HmqRUdzT7yowsCbCKcvvhhnu9uPr69InjcYTlhnxOkTss7DwRcK09Lrj2t39hV98wXDNHbH5+409fhYuaeV93e3jrqNAsHBtCc4Z5t6fGTaDKik/vXA6vbxq68lEAgOzXHthGyo6WLqSMSKRkKw+VkoXjGsYdq9HbS4W8i3FR6yj0qCaSlKSNa4IqnoyZ1P2q7/jdpbmLQmPlP8Ge5YcweyLB/5AEEM+9tdvLqpkefW1LK5rjuukOBok2kzcN6s/hyB1fs7WX5QcTGAk0v626amW9AcpLpw3qwsMvtyPrLsRs6YFlt4S6uWKBYx38Mi3arn4nmxhfjUKomp6RbCEZmWXj+fmRMvszu/IImNdT2cMV0UQxOMPXMLkuLaPjs7G71Wxa2nTuWrK6byjdNLOLdC5CoJBBOR49YJCYUj7GhyjkzC2r53wJgEyYXDGmZN02qmOqaiPkJSe3lykI/qJ0BIVt4CUva+gxQKjNp7LMtdRqevk7drR75A4rFMVZuLqx5dzdee38j3X97KxX/5hNX7O8bUBr1WzbfPLOOyBbno1CrSLHpOK0/n9tNLsOg1pFn13H3pbOYX9t9IlGfaeOL6hZSkW9CpVVw6P5dvn1kWTUw36tT84NxyLpybjU6toizTyt9uWER5pnVMP9uxhk6j5tZTp3LFonz0GhXFaWYeu3YB07NsrNnfwWf/9DE1HR6uOaEAi15DulXPTy+Yzs6mHn570SwWFoo6DIKxZ0G+g99cOJNMmwGTTs0NSwtZXprGr/67k/vf3cd97+zj8Y+rSbOIfDGBYCJy3Cam72zqJdWiH36l9HBQ2QWZecmwhukN9LKnaw/nTznviH1LkgL8fbcFp1/Cph+/HYKgKQWfPYek/R/SWXLaqLyHSlJxaeml3Ln2Tk7OPRm9WlxMjoZ1NZ00dveHPoUiMn98ay+zcx2Yh3vOD4LCVDO//twsvn5aCSa9hiSTjkVFyVy2IA+NWiLNGutMq1USJ5Wk8eJNJ+Lxh0i3GtBqYp3yojQLv7u4gm+fWYZFrxF1REaIghQzv/jsDG5bMRWTVk2SWYcnEOKPb+8lFJH5x/p68pNNXL4wjyXFKczMtSEhKZKpAsE4kGYzcuXiAhYVJRMMRShONfO9V7bhC/bnLvV4g7y7q5VZuY7xM1QgECTkuN0JWVvdSWnGSOyCvA2mFEganszvJ42fMsVRjO4obrJ1aihJCrKqafwv/j15i0jf9q9RfY/pKdPJMmfx1I6nRvV9jiU6XPG7U009Xvyh8JjbotWoyEkykdTnLEiSRJbDGOeADCTJpCMnyRTngBxAr1GTk2QSDsgIo1WryHEYownmgVCEph4lF8SgVdHY7eWxj/azo8lJhtUoHBDBhGBqupVp2XZQS9R2euJer0+QzyQQCMaf43Yn5NOqDkozhhnCEQ7A5ueg4rJhDdPt72ZX507OKTr3qI+ZnhLgwzojZxaO7+TamzmD9B3/xti+D2/qoRPqh8ulpZfy2zW/5bPFnyXNFJ9XIIhlfoJY6asW55NsHtmdpIYuDxtqu2lx+pieZaMo1cyOJqXWRHGahTl5DlIHSOdGIjJbG3rYXNeNQadibl4SJcP9HQpGDYdJx00nF+P0BenyBNFpVEhASbqZfa29TE0XfzvB+LK2upOt9T14AiFm5ti5YWkh6wco7gGcMzNznKwTCASH47h0QiIRmTX7O/ns7PhEy0Gx+39gyQBH/pH7Hob361ZS4ijFMIhQo/KUAP/cZ8YdlDBrxzFpW6Wmq+BEMre8xP4V3xu1t8kwZ3BSzkncve5ufnfy70btfY4VZuc6ePDq+dzxv510eYJcv7SQC+fmjuh7tDh93PbcRjbWdgOwoCCJkgwLz62pi/a5YmEePzx/ejTscV1NJ1c+sppQX5J8kknL8zeeIDT8JzDpNj0//tc2DugapFn1/PpzM7n0wU/F304wrqzd38Etz2ykzaWoZKlVEn+5ah4/+8x0Hni3Eq1a4ptnlrJI5CwJBBOS4zIca0eTE6tBQ8pwktWCXtj6Akw9fVi21DhraHA1MC1lcAUOjRqZqY4gn0yAmiHdBYtxVH+C1tU+qu9z3pTzWNW0ivUt60f1fY4F9Fo1Z8/M5OWbl/LGN07maytKogpTI8XOJmfUAQE4qSQ1xgEBeG5tHVVtLgD8oTB/eb8y6oAAdHmCfLh3dM8bwdDp8vj583uVDBRWa+v1U9nqQkbmo33ibycYP9bVdEUdEIBwRObBlZWcNyuL175+Ev/+6klcMj8Pi0E7jlYKBIJDcVw6ISv3tDIrxz68Qba/AklFYBu69F8wHOR/+//HvPS5qKXBb0pVpPl5p8Y05PcfKSI6Mz2588nc/OKovo9RY+Tyssv52Sc/IxAePUWuY4kks44MmwFpGAU0D4UnEJtfEjmEjLK3r18oLNPsjK8T0tob3yaYGHgDYTrc8b+1bl8Qq15LW4I6DQLBWNHjja8P1OEO4AmESLMahrfQKBAIRp3j0gl5e0crFcNRyvB0wI5/DnsX5J3at0k2JJNjyTly5wRMSwmwp1NLu3f8/4xdxctJ3f0GWvfoysDOz5hPsiGZhzY/NKrvIzgyU9MtGLT9516r009RSqxTnJtkpLCvIKhZr+HaEwvjxjmlNH1U7RQMDm8wxKqqDh54dx+b67q5ZH58GN+MbDt1XV6Wl4r8LMHYUdfp4ZWNDdz79h4+2NOWMPftknm5FKSIukECwWRg/O9ex5i2Xj97WnuZkT2MOOa1j0HuQjANPc50c9tmqntqmJcxf8hj6NRQkRbg7erx3w0JGez05C0ke+3fRvV9JEniqmlX8eKeF9natnVU30tweEozrDz9xcWcUJRMillHWYaFb5xRyorydJLNOk4pTeM7Z5Vh1qmjx5w+LYOfXTCdLLuBqekWHrx6HvMKHOP3IQRxvLerjc8/vIo739zNzc9sJMWs5RunlZBpM1CaYeHuS2ezdn8HD109n7n5jvE2V3Cc0Nzj45ZnNnD7C5v449t7+cJf1xAKR7jn8jmUZljItBn4+mklnDFDLGoIBJMFaTJWol6wYIG8bt26IR375KfVvL2jhZtPGaKSU9Mm+OAuWPp10Axtq3d3527erH6TFfkrsOqGpy5T36vhuZ1W/nZeC+qRj7gZFKqAhynv38muC+7Cm1o8qu+1tnktr1a+yt8v+Puwv8MjcNTf6nDOy8mM2x/C7Q/R0uvngvs/Yl6+g/JMG7tbellf08W/bl3K7DxHzDEdLj8alSQkdofOoH7tR3tudrr8fOaBj6nvilXde/L6hRSkmjFoVGjUKvG3ExyOUZkz39/VynVPrI1pM+vUvPmNk4kg4wtGhNKe4HCM8x2SIBHH3U7IC2vrOLE4ZWgHB73w8X0w7YIhOSAyMmuaVvNmzZucnLd8RG6ec60hLNoIn06ABPWIzkRb2VkUrrwbIqNbj2Jh5kLKksv4/offJyJHjnyAYNQw6zWk2wwE+mqQbKjt5tk1tVGZTF+C2iQpFr24iZ2ABMIyzgRx9i29fgpSzGTYjeJvJxgXfMH4ecQbDOMPR8hLNgsHRCCYhBxXTsjW+h7aev1U5DiGcLQMqx5Q5HjTpw362AZXPc/seJZt7Ts4veB0kvRDsSExy3K9PLfTwkTY1OrJX4QEZG18btTf6/Kyy2nxtHDXurtG/b0ER6YwxUzJQQVAC1NMFKWYx8kiwWDJsOm5bmlRTJtWLVGeKW7wBOPL1AxLTGgnwGfnZJOTZBwniwQCwXA5ruqE/Pn9fZw5IwOVagi7cjv/A627YPFNR+waCgfpDjjp8LbT6GpkX08loXCQ8uRypjimII3wruD01ADv1Rn5qMHAstxxVhqSVDTNvoyCj+7HnV6OM2/BqL2VVqXlltm3cOe6OzGqjdw297ZRUYESHB0pFj0PXDmPxz6s4oO97SwtTuHLJxeTbhv/XTrB0SFJElcsysOoVfHM6lpyHEZuP72UGdnDVBMUCIbJ1HQrz3x5Mfe+vZfdzb18bm4On1+Uj16jPvLBAoFgQnLc5IRsquvmi0+s5a5LZ2PQDnLSqnoP1jwCi26MSUbvDfTS5Gqm1dtCu7eDbn8XTn8vgUgAi8aMTW/DoU8i05xBijFlxJ2PgVR2a3lpt4WHz24d3+KFfRg7qshe/zR7z/0V7ozpo/pePf4e7ll/DwsyF/DDxT9Eqx5RTXiREzJIguEITm8Qm0GLVnNcbbaOJaOSEzKQTncAvVaFWXdcrVUJhs+ozpm+YBi3P0SyWScWnQSDQZwsE5Dj4uriCYT41oubuHxh3iAdEBm2vgw7Xob51+HRGqju2Mn+nipqnbUEIgFSjanY9XaSDckUWPMxaU0YNIZRdTgSUewIUpYc4K41Dn68pIuhbPaMJN6UKTTPvpSS135EzfJv0DXl5FF7L7vezncXfZfHtj7GVa9dxa9O+hWlSaWj9n6Cw6NVq4Q+/zFAslnkfQgmHgatevALiQKBYEJyzDshbn+Irzy1nvxkEydNTT36Azsriax+iKCnnQ15FeyueZ0ufzcZpgwyTBmclHMSdv3EClE4t9jNE1tt3LnGwe0LutGN8zztzphGw6LryP/4zyRVfkD94i8SGEZxx8Nh1Bi5dc6trKxfyQ3/u4GTc0/m2hnXUpY8uEr0AoFAIBAIBILR55h1QjrdAd7a0cx97+xjWpaV65YUHWLrVsYT8tDjasHVvpNI8zYczduxeHtYbdRTZ88hlQizUmeRYkxFJU3c8BKtCq6d6eSlPRZufCOdy8tdLM72kWwYP/UonyOf/SffTnLlSmb84ybc6eV0FS7BnTEdnyOPiHbk8gUkSeKUvFNYlLmId2rf4StvfQWbzsZJOScxO302Ux1TyTJnYdKOf10VgUAgEAgEguOZSZkTIklSG1CT6LWMK3471ZA/K7pFIYeDcqClKqDL1KrVZlXU6dLKEWb546UoD+CWJGQZlP8mPhJIA22tlIukELG5EX/T3xy2Su4xt+0AemRpBuFDenE/wOJ7UTKGDvW6HJG1kko69B/tYCQkXYbOqDaoD+s5dn3U1drwaEPdIV5ul2X57KN6u8OclyNMKtA+Bu8zXCaDnZPBRoi386jPSxjTc/NQTIbvWdg4MhhkWZ55NB0HcV5Ohs99OIT940sqsGswc6ZgbJiUTshgkSRpnSzLoyfTNAEQn/H4YbJ8D5PBzslgI0weOw/FZLBf2DgyjIaNk+FzHw5h//gy2e0/lpm4sUUCgUAgEAgEAoHgmEQ4IQKBQCAQCAQCgWBMOV6ckIfH24AxQHzG44fJ8j1MBjsng40weew8FJPBfmHjyDAaNk6Gz304hP3jy2S3/5jluMgJEQgEAoFAIBAIBBOH42UnRCAQCAQCgUAgEEwQhBMiEAgEAoFAIBAIxhThhAgEAoFAIBAIBIIxRTghAoFAIBAIBAKBYEwZEydEkiS1JEkbJUn6T4LXTpEkqUeSpE19j5+MhU0CgUAgEAgEAoFgfNCM0ft8HdgJ2A7x+oeyLJ8/RrYIBAKBQCAQCASCcWTUd0IkScoFzgMeHakxzz77bBkQD/EYi8dRI85L8RjDx6AQ56Z4jOHjqBHnpXiM4UMwARmLnZB7gO8C1sP0OVGSpM1AI/BtWZa3H9xBkqQbgRsB8vPzR8FMgWDwiPNSMFER56ZgIiLOS4FAcIBR3QmRJOl8oFWW5fWH6bYBKJBleTZwP/DPRJ1kWX5YluUFsiwvSEtLG3ljBYIhIM5LwURFnJuCiYg4LwUCwQFGOxxrKfAZSZKqgeeBFZIkPT2wgyzLTlmWXX3/fg3QSpKUOsp2TRr8wTCN3V56fcHxNkUgEAiiNDu9tPX6xtsMgeCoCIUjNHV76fYExtsUgUDQx6iGY8my/H3g+6CoYKGEWl09sI8kSZlAiyzLsiRJi1Aco47RtGuysLellz+8tYd3d7UyM9vOD8+bxryCpPE2SyAQHMe0u/y8tL6ev6ysRKdW8e0zyzhnZiZWo3a8TRMIElLX6eGxD/fz4vo6suwGfnz+dJZOTUWrFlUKBILxZFx+gZIk3SRJ0k19Ty8BtvXlhNwHfF6W5eM+iajHE+Db/9jM69ua8YcirK/t4tq/rqG63T3epgkEguOYd3a28NvXd9HtCdLa6+e7L21hXU3XeJslECQkFI7w8AeVPPFpNZ5AmMo2Nzc8sZYdjc7xNk0gOO4ZMydEluX3D8jwyrL8oCzLD/b9+0+yLM+QZXm2LMsnyLL8yVjZNJGp6/Kyua4npq3XH6JKOCECgWCcCITCPLu6Nq79zR0t42CNQHBkWnr9vLiuPqYtIiuRBgKBYHwRe5ETFJNOjV4T/+ex6seqtItAMHhcARffWfkdLn71YlY3rR5vcwQjjFqlojDVHNeem2QcB2sEgiNj0KhIt+nj2i0GcS0VCMYb4YRMUApSzHz7zLKYtgtmZ1OSYRkniwSCI/PDj3+IO+jmrMKz+Nb736LZ3TzeJglGELVK4volhRi0/ZeOZLOO06elj6NVAsGhSbHo+en5M5Ck/rYZWTZm5djHzyiBQACMXcV0wSBRqySuWJTPzBwb1R0eMmwGZuXYcJh0422aQJCQNU1r2N6+nV8s/QValZbK7koe3vIwPznxJ+NtmmAEmZOfxCu3LGVHoxOtWmJGjp3iNLE4Ipi4nFyaxss3L2FvSy82o5ZZOXZykkzjbZZAcNwjnJAJjMWg4cTiVE4sHm9LBIIj8+jWRzl3yrloVYpK0hkFZ/Cjj3/EtxZ8C7M2PoRHMHmZlmVjWpZtvM0QCI4KnUbF3Pwk5uYLdUmBYCIhwrEEAsHw2PAkkd/lc8WW1zkxbV602a63U5ZUxru1746jcQKBQCAQCCYiwgkRCARDp3ETvP0zPig/nUKVnvwtL8W8PCd9Du/UvjM+tgkEAoFAIJiwCCdEIBAMnXd+DhWX845rP/XTziNj68uoAp7oyxWpFaxqWkUoEhpHIwUCgUAgEEw0hBMiEAiGRkclNG6kPWcuXf5OUtJn4E0qJGn/R9EuNr2NVGMq2zu2j6OhAoFAIBAIJhrCCZkgBEMRqtvd1HV6EAXjBZOCzc9D0XK2dO5kir0YFRK9WRUk73svpltZUhlrm9aOk5GCkSQQCrNfzFOCCUZdp4f97W78ofB4myIQCAaBUMeaADR2e3loZSXPrK5Fq1bx9dNLuHxhHklCjlcwkdn+Miy+mc21r1NkLwTAlV5OxtaXkUIBZI1y/hY7itnQumEcDRWMBA1dHh54v5IX1tah16i4/fRSLluQh92kHW/TBMcpvd4gL2+s58439uAJhLhkfi5fXVFCXrKQ3xUIJgNiJ2QC8NrWJv72aQ2hiIw3GOZ3r+9i7f7O8TZLIDg0HZXg7SaUUsSert3k2woAiOhM+G1ZWFp2RLtOdUxlc9tmsXI+yfnXpkaeXV1LOCLjCYT59Ws7WVcj5inB+LGxroufvroDlz9ERIYX19Xz93V1Yq4RCCYJwgkZZzyBEC9tqI9rX7mnbRysEQiOkr1vQc58qp21OAwOzJr+lUdPchHWxs3R50mGJDQqDQ2uhvGwVDAC9PqCvLQh/u/3SWXHOFgjECisr+mOa3t5YwNdnuDYGyMQCAaNcELGGb1GzYxse1x7aYaoQCyYwOx9E7LnsLNzF3mWvJiXvMmFWJu2xrRNsU9hW8e2sbRQMIIYNGqmZ1nj2qekiiKUgvEjL9kY11aWYcWsU4+DNQKBYLAIJ2ScUaskrltSiM3Yn55TlGpmWUnaOFolEByGcBDqVkNmBbs6d5FrjXVCfI58zG17QI5E2/Kseexo33HwSIJJglaj4ssnT8Gq75+npqZZWDI1ZRytEhzvLCpMYXqWLfrcrFNz24qp6LXCCREIJgMiMX2MaOr20u0Nkm7Vk2LRx7w2M8fOP29Zyp6WXrRqFeWZNnKS4ld4BIIJQdMWsGQQ1lup6q7ktPzTYl4O6y2EdSb0PY34HbmA4oSsblo9HtYKRoiKXAf/uk2ZpzQqFVkOA7IMwXAErVqsZwnGhvouD72+EFl2A/kpJh67dgE7m534gxFKMqxMTRdRBALBZEE4IaNMJCLz/p5WvvuPLbS7AhSnmfnDZXOYneeI6TclzcKUNDF5CiYBNR9D+nQaXA1YdVZMmniH2WfPwdy+N+qE5FvzeWrHU2NtqWCEmZJmQa9R8ce39/LShno0KokvLSviiydNIfWgxRWBYCQJhCK8uaOZH76yjR5vkJnZNu68dDbTsmxkOcSinUAwGRHLV6NMZZuLm57aQLsr0PfczVef20B7r3+cLRMIhkj1h5A+jX1de8m2ZCfs4rdmYWrbG32eZEgiEAnQ4RWJzJOd17c184/19X27IDJ/eb+K1VXi7yoYXXY39/LV5zbS41WSzrc1OvnhK1txekUSukAwWRFOyChT2+khEI4c1Oalqcc7ThYJBMNAlqF+LaRPZ0/3XrLMh3BCbJmYOiqjzyVJIt+az97uvQn7CyYHvmCYf26KV8l6X6j5CUaZmk43ByvvbqjtpsXpGx+DBALBsBFOyCiTYo4vOGjVa7AbRYEvwSSkswrUOjCnUtVdSbYlK2E3vzULY2d1TFu2JZu9XcIJmczo1Crm5SfFtc8YkBwsEIwGia6lGTa9uJYKBJMY4YSMMiUZVm47dWr0uSTBry6cSX6KkLYUTELq1kDaNFwBF85ALynG1ITdgqYk1AEXar8r2pZlzhJOyCRHpZK4YlE+aQPyP0ozLCwvSx9HqwTHA9OybFy5KD/6XKOS+O1Fs0i3GcbRKoFAMBxEYvooY9ZruGl5MaeWp9Hq9JOfYqIkPV5v/2io6/TQ7QmQbjWQYRcTr2AcqF8DKVPZ79xPtjkLFVLifpIKvzUTQ1ct7szpgLIT8vr+18fQWMFw6fEGqe/yYNCoKUgxoVGrmJZl4+VblkRVssoyLWTaRWKwYHRxmHR875xyPjc3m053gMIUMyUZVoKhCNWdbgKhCPnJJqwGsTMiEEwWxsQJkSRJDawDGmRZPv+g1yTgXuBcwANcJ8vyhrGwa6ywGDTML0ge8vGRiMw7u1r59t830+MNkmHTc/8Vc1lUJDT6BWNM3VqY9wWquveQbso4bNeAJR1jd02/E2LOZn/PfmRZRvnZCyYyla29fO+lrayr6UKrlvjqihKuXVKA3agjL9lEXrJpvE0UHGfYjdqY616n289jH+3noZVVhCIyS4pT+PWFMylKFUqTAsFkYKzCsb4O7DzEa+cAJX2PG4G/jJFNk4bKNhe3PrMhqgrS4vRz6zMbRXK7YGwJ+qBjLyRPoapnP1nmzMN2D5hTMXTWRJ9bdVYkJDp8QklpohMMRXjogyrW1XQpz8Myf3hrD5vresbZMoGgnw213TzwXiWhiJKx/kllB0+vqiUckY9wpEAgmAiMuhMiSVIucB7w6CG6fBZ4UlZYBTgkSUqc7Xqc0tDtjVPYanP5aekRqiCCMaRlGzjyQKOnxllNpuUIToglHWN3bfS5JElkW7Kp7qkeZUMFw6XLE+CtHS1x7XtaesfBGoEgMVvquuPa/retmR5vYOyNEQgEg2YsdkLuAb4LRA7xeg5QN+B5fV9bDJIk3ShJ0jpJkta1tR1fcpCpFj0HR6+YdWqSEqiFCMaW4+q8bFgPyVPp9ncTlEPYdPbDdg9Y0jB018e0ZZgz2O/cP5pWCvoYzrlpNWipyHXEtYsQLMFwGck5szhBdfR5+Q7MepHuKhBMBkbVCZEk6XygVZbl9YfrlqAtbi9VluWHZVleIMvygrS0tBGzcTIwNd3CD8+dFn2uVkn87uIKCoTC1rhzXJ2X9esgpZhqZw1Z5sxDpaRHCZpS0bnakMKhaFuGKYOq7qrRtVMADO/cNOrUfOvMUhym/iTfM6ZnMCfv8I6nQHAkRnLOXFiYzLKSfoW+VIuOm04pRq9RD9dMgUAwBoz2csFS4DOSJJ0LGACbJElPy7J89YA+9UDegOe5QOMo2zUh6PEE2NXcSyAcoST90AozBq2aq07IZ3FRMm29frKTjBSnicQ7wRjTuBFOvI3qrm2kGY988yCrNYSMdnSuFvx2ZXMz05zJhpZjSnfimKUi18Grty6lqs1NkllLICzT5Q7iMOrQa2Nv8ty+EPs73MhAUYoJi1AoEowB2Q4j91w+h32tLnzBMMXpFnKTEu/W1XS42d/uxmrQMD3ThlHslggE486o/gplWf4+8H0ASZJOAb59kAMC8CpwmyRJzwOLgR5ZlptG066JQGVrL/e8vZd/b1E+6vwCBz/7zAxm5TgS9jdqNcxKEB4hEIwJ/l7oqYOkAvZX/5tCe+FRHRYwp6LvaYg6IRmmDGqcNUc4SjBRyE8xEwhH+NaLm9lc34MkwXUnFnLriqmk9tUKaejy8Kv/7uT1bc0AnFaezs8+M528ZLFTKxh9Uix6UgbUrUnEuupOvv33zVR3eNCoJL60rIjrlxaSYRPS0gLBeDIuxQolSbpJkqSb+p6+BlQB+4BHgFvGw6axZlVVZ9QBAVhf080/NzYQiRwqdUYgGEeatkDyFFBpqHPVknkEed4DBE0pGHoaos/TTem0eFoIhoMJ+3d7Atzx+i6uemQVv//fLpy+xP0EY0MoHOGJT6rZXK+oYskyPP5JNRv6VLMA3tvdFnVAAN7Z1cqbO1rH3FaBIBHd7gB3vbmb6g4PAKGIzIMrq9hUK5TeBILxZsycEFmW3z9QI0SW5QdlWX6w79+yLMu3yrJcLMvyLFmW142VTePJhtquuLaP9nbQ7RE3XYIJSONGSJ6CK+DCE/RiNziO6rCgKQn9ACdEo9KQYkihwdUQ13dvSy9n3fMB+9pcnFicyo5GJxf/+RN6xG9i3HD6gry7M96h2N7ojP77vV3xr7+5vTmuTSAYD1p7fayrjr/eNnQLiXuBYLwZl50QAczMjk/wnF/gwCZiqQUTkYZ1kDKVWlcdGab0Q1dKP4iAKTVmJwQUhaza3tqYtuYeH1c/upqL5+Vyw9Ii5hckcePJU5iSZua7L20esY8hGBwWvYbFRfGFVkszrNF/n1gcXzR1YLKwQDCeJJt1zMy2xbVn2A4fwiUQCEYf4YSMEycUp7B4Sv/FvTDFxKUL8tBoxJ9EMAFp3Kg4Ic5a0kzpR31Y0JyC3hmb4pVmTIupFRKOyNz67AaWl6WxrKQ/4V2SJK5cVMCW+h4+3HuMyx9PUHQaNTcuLybHYYi2nTMzk/kFjujzM6ZlMDev//nMbBvnzRKlngQTg1Srge+eXU7yAEn7i+flUJErlN4EgvFGyEOMIhtrumjs8ZJm1VOR48Cg61eUmZZl44+XzWZXUy/BcITSDCtFCRSvajrcNPV4STHrKUo1o1EfW05KMByk2llNt7+bLHMWudZcAJx+J9XOaiJyhEJbIY6jDP8RjALebnC1gj2Pmro3jkoZ6wABUzJ6VwvIEZCUczfNlEa1szra57EPq/AHw3x2Tlx5IHQaFZfOz+WuN3Zz0tRUpIML5ghGnWlZNl66eSlVbS70WjVT0y2EIxHWV3ei06rx+kN89+wy1JKEyx+iNMOK3aRlc103wXCEolTzEROHBcOj09tJtbManVpHka0Is04RBejx90Qd/gJbwTE5j7r8IaraXPhDEYpSzKRa9dR3edjb0otapaIs08KSqak8dcMiqjvc2AxaSjOsZNgNRx78OKfZ3Ux9bz1WnZVCWyF6TfzveOA1PNucTY41fh4XCA6FcEJGiX9vbuT/XtqCOxBGp1bxg/OmceGcbOym/tWYbIeJbMehi399tLeNm5/eQK8/hFYt8YvPzuSiuTlx8piTFV/Ix0t7X+KutXcRkkPYdDbuPfVesixZ/HrVr/mw4UMA5qbP5ZdLf0mBrWCcLT5OadoEKcWgUlPXW09pUtlRHypr9IQ1RrSeToJmJUQnw5TBp42fAtDY7eWB9yv52QUzUB3CwVhclMI/1tezobab+QVJw/44gsGTaTeQ2XfTVtXm4vYXNrOkOIVPqzrY1Fe1elFRMjOzbWxv7GFncy+vbVXyQqZnWbnvinlMTVBYTjB8qrqr+M7K77Cnew8A5xadyzfnf5NgJMjPP/05q5pWAbAwYyE/X/pz8qx5hxtuUtHq9PH7N3bxj/VKyOfUdAu/u2gWP//3drY2KHlLy0pS+eqKEr723EaanT4kCb5y8hRuWl6MwyQK/h6Kbe3b+Oq7X6Xd245KUnHjrBv5wowvYNX1h2L6Qj7+vvvv3L3+bsJyGLvezr2n3sv8jPnjaLlgMnFsLatPELbWd/Pjf23DHQgDEAhH+OV/drCjyXmEI/tp7PZy+wub6fUrhd6CYZkfvrKVfa2uUbF5PNjXvY/frfkdIVn5jM6Ak9+s+g0f1H0QdUAANrZu5M3qN8fLTEHDBkguJhQJ0eZpJdU4uHh/JSSrP1E53ZROXW8dAL95bSenT0uP3uAmQqWSOLU8nac+rR6S+YKR5ZWNDTR2e/EGw1EHBGDN/k60ahUqlRR1QAB2NPXy/JpaIpG4GrSCYRKOhHlh9wtRBwTgtf2vsaF1Ax/Wfxh1QADWtqzl3dp3x8PMUWN9TVfUAQHY1+ri6VU1hAeITKpVEne9sZtmpw9QFN4eXFnFtgahjnUoegO9/Hb1b2n3tgMQkSM8uOVBdnbsjOm3t2svv1/3e8Kycq/T4+/hRx/9iA5vx5jbLJicCCdkFGh1+uNUrsIRmaYe31GP0eHy0+byx7RFZKIT6bFAkyu+HIxarWZ18+q49pX1KwlHwmNhluBg6pWk9CZPM3a9Ha1qcBuoQVMy+t7+v3WqMZU2bxub6jr4tLKD8yuyjzjGySVpvL2zFbc/dMS+gtHDFwzz7q5WitPNCW/idjX34gnE/07f39OGOyD+diONO+Tm48aP49q3tW9ja/vWuPYP6j8YC7PGjEQLe2uruyjL7F+tn5ZpY30CNcrG7mPnWjrS9Ph72NK+Ja692ROretfsjlfBq3fV0+nrHDXbBMcWwgkZBdJsehymWJUrtUoiaxAxqCkWPWkHxVGrJA67YjzZyLLEJ6+Gw2EWZy6Oaz8592TUqmMjDG3S0bgRUkuo760bVFL6AYLGpJjkdI1KQ7Ihmd/9bxsXzM7GcBThhTajlrJMK2/uENKv44lBq2ZFeTqVrW5m5MQn9pZnWjHp4v+ep5SmYdaJ6N+RxqwxszR7aVz7zNSZzEqbFde+LGfZWJg1ZkzPile9WliYxO7m3ujznc1O5uU74vplO46da+lIY9fbmZUaf/5kmWOv2ZnmzLg+uZZckg3xinoCQSKEEzIKVOQ6+OVnZ2Luuxjr1Cp+dN60hBPmoch2GPnj5bOx6pULt1Yt8esLZzE1QfL6ZGWqYyrfW/g9NJLyGW06Gz844QecnHcyJ+WcFO03J20OZxWeNV5mHt/0tkDABdZsap11pBji5ViPxMFOCIBZLmV7o5tTy47eqVlclMyrmxsH/f6CkeXCuTlkOwyYtGpmD1AYWliYRCgiE47InDur/+ZkepaVzy/KR6USogIjjVql5rKyyyh1lEbbzik8h3np81iWs4zFWf0LOgsyFnBawWnjYeaoMb8giUvm9ydCT023cPUJBQw81UKRCN85q5xMm+J0SBLctHwKMxM40QIFq87KDxb/IBp6q5JU3FRxE+XJ5TH9SpJK+O7C76KWlHsdm87Gr076FSnGwV8nBMcnkixPvjjdBQsWyOvWTeyahpGIzMbaLhp7fKRZ9czItmI16HD5Q1S2uej1hsiyG+jxBvCHIhSnWUi3xa/M1HS4aez2kmLRM+UYV8fKtmSTY1EuKBNIHeuo75wmw3k5aHa9Bh/9AU77KXeuu4vy5HJKHFMHNYSpbQ9J1Z+w63P3RNu+8fwmsq0pfPOU5Uc9jtsf4mvPb2TtD0/HrD/uV9UHdUc/0ufmzqYeqtrc6DVqHEYNEcCoUxMMyUxJM6NWSVS1uYU61hhxOHWsGmcNsiyPpTrWmM6ZdZ1u9rS48AbDTE2zUJ5li6pjqSSJ8iwrGTYje1p62d/uwmZQdlWTzeKcPBLN7mbqXfVYtceEOpZYBZmAHPdX8tHi7Z0tfPW5jfhDEdQqiZ99ZjpnTc/kgff28bdPawBIMmn52mkl/Oq/OylMMfHg1fMpGVAEDKAgxUxBink8PsKYoFVrKUkqiWu36W1UpFWMg0WCGPryQQAaXA1DCucImpLR9bZEn3e5w7S2ZzCzsPYwR8Vj1msozbDy4d52zp4ZHwYgGBvW1XTy3b9voardDShFVn9y/nRm5Thi+s3Oc8QfLBgVko3JJBvjQ2DsevsxPY/ua+nl16/t5L3dSh2hbLuB+66Yy4LCZHKT+pUnN9d1c/0Ta+l0BwC45oQCbj+jRDgiRyDTnJkw5Gogh7qGCwRHw7G1rD5BqO308O2/b8YfUiQ6whGZn/5rOxvruqMOCECXJ8grGxuUGOs2Ny+srRMKMoKJRf0aSC3FFXTjC/mw6Y8+pPAAQaMDrbcL+oQF3tnmpSDDT1dg8Pkds3PtvCXyQsaNcDjMvzY2Rh0QgPU13ayqEomogrFnXW1X1AEBaOzx8deP9+MdIGDh8gX55X92RB0QgKdW1bCt4ejVKgUCweggnJBRoNPlx+mLVYKJyNCSQB1re6Mzmufx4d52vEGhACWYIETCfUnppTS4Gkg3paEayo62SkNIb0Xnbiciy7yzzcecAi2t3tZBDzU3P4n3drcxGcNIjwWc/hAb6+KVhrYKuVPBOLC3pTeubXNdDx3ufmXJHm8wRkr6AM2DUKsUCASjg3BCRoF0m4EUc2wRJI1KIifJGNd3fkES2xuVC/iZMzISKssIBONC224wOsBgp6G3npRB1gcZiCLT28zO+iBatURJmo1ObwcykSMfPIAMmwGDVsXOpvibD8Hok2TSs2RKfNKpKCIpGA+mZ8Unl59YnEKatT/MKsmsY8nU+HM2N8H1WCAQjC3CCRkFsh1G7rtiLkl9Mr0mnZo/Xj6HeflJfOvMUjR90h0FKSbOnJ7Bh/vaWVSYzEXzcpEOUTVaIBhz6lZD2jTln676ISljHSBoSkLX28LKnT5m5GnRa/To1Qa6fd2DHmtWjp2Vewa/iyIYGc6ZmcXCwn6n4+yZGSwsFJKcgrFnQUESly3I5cBlc0a2jatPyEev7U93Nek0fP+caRSmKjkiapXEN88oFepYAsEEQCSmHwFPIMTeFhcdLj+5ySamplkOKzVZ1eaiusNDslnLSzcvocsTJNmspTDFjCRJ3HRyMWdOz8TtV9SxujwB/nnLUgpTTdiNukOOO9Hp8nVR2V2JL+yj0FZIrjV3vE0SDJfaTyFVSTis761jQcbCIQ8VMthR97SwptLPl1co4gtJBgetnjaSBqkpPzPbzgd72rn5lMGpdAmOzP6++ctm1FCSbsVmjK131NDlpdcf5OefmUGL04dWraIk3UKGXawqjwW1zlpqnDWYtWamOqYOKUfrWKIg1cytp0zl3FlZ+INhClJMlCfYHZmWZePvX1lCXacHs17DlFQzWo1Ygx1v6px1VDurxfl8HDMoJ0SSpCVA4cDjZFl+coRtmjC4/SEe/qCKe9/ZCyj1Pv581TxOn56RsP+a/R1c//ha3H0Vg69YlMd3ziqLUeDQalQx1VyzHJP/4t3ibuGXn/6SlQ0rAUjSJ/HgGQ8yPWX6OFsmGBa1q+Dk7yAj0+hqIrVwGOFYxiS2NEmkWFQ4TMrF36530OZto4yyQY01PdvGn1dW4guGj6rQoeDoWLu/k+seXxOdvy5bkMv/nVMenb92NTm57ok1NPco8faLCpO5+7LZwgEZIza3bebmt26mN6iEIp5XdB7fWfAdUkzHb02G3c1Ofvyv7azZrwgjpFn0PHDVXBYVxX8naVZ9TJiWYHzZ0raFm966KXo+n1N4Dt9d+F1STUO/zggmH0e9FCBJ0lPAXcBJwMK+x4JRsmtCsKelN+qAAATCEb770hYau71xfbs9AX78r+3RCzjAc2vq2NF47CtwbGnbEnVAALr8XTy4+UF8IZH4N2lxtYK3Exz5dPt7UEkSZq3pyMcdgqAxiZXtqZRm9a+s23U22jyDD6sy6TQUJJvYUBOfIC0YGt2eAD95dVvM/PXiunq29ykIhcIRHv+4OuqAAKyp7mTV/o4xt/V4xBVw8fs1v4/esAH8d/9/2d65fRytGn/WVXdFHRCANpefRz/cj9sXHEerBEfCHXRz97q7Y87n16tfZ3vH8X0+H48MZidkATBdPo5kaVqd/ri2TneAbk+A7IN2MJzeILub45NlW3rjxzjWqO2Nr/ewpW0LroALgya+AKNgElDzCaTPAElFfW89aca0YQ0XNCbxobuQSwY6IXoHze6Wwxx1aKZlWvmksoMlU8Wq2Ujg9IUSJvsfmL88gTDrauJleHc29sL8UTfvuKc30Muuzl1x7W2etgS9jx+q2l1xbdsbnXR5ApgN2gRHCCYCvf5ednbujGtvHcKilGByM5igyG3AcVUhLC/ZyMHpHwUppoSVzVMsek5KcENUkDz01ePJQllyfDjNivwV2A0i8W/SUv0hpCtJ6Q2uBpKNwwv52BtMR5IjpA6oxZlkUMKxhsK0bDsf7Wsflk2CflIsOk4uOfT8ZTVoOHtmVtzrAxPUBaNHkiGJk3NPjmvPs+aNgzUTh4MLZAIsK0kl3SZCBCcySYakhIVv823542CNYDw5ohMiSdK/JUl6FUgFdkiS9IYkSa8eeIy+ieNHSYaVez8/F6te2TDKTTJyz+VzSLXEx5Wa9Rp+dN40yvvyPQxaFb/47AymZR37iVazUmZxy+xb0KiU72le+jyumX4NWpVYiZq07P8AMmcBSlJ66jCdkHVtZmapa9D4+1cuHXoH7d6hORKlGRZ2N/fi9oeO3FlwRMw6DT84bxrTspT5S69R8fPPTGd6tjJ/SZLEpQtyOaVM2RFTqyS+vKyIhUVCFWssMGgM3DrnVqYnK3l2OpWOb83/1nGfdze/wMH1SwujipOLCpO4cnE+OpF0PqHRa/TcPOdmZqTMAJTz+Zvzvxl9Ljh+OJpwrLuGOrgkSQbgA0Df917/kGX5pwf1OQX4F7C/r+llWZZ/MdT3HEm0ahUXzM5mdq6dbm+QLLuBNOuhw4tKMyz86nMzqWxzYTdqybTp+e/WJgqSjcgydHuD5CWZKMmwxk2StR1u9ra60KhVlGdYybBPnjAmu8HOlyq+xFmFZ+EP+8m15GLVW498oGBi4m4HZyMkFwNQ72pgac7SYQ25rtnAMkM7Wk834b4dMrPWjD/sxxf2YlAPbuVSr1EzJc3M+pouTi4dXqiYQKE808azXzqBhi4vZoOSd3NACXBbfTe7W1xcPC+XW5YX4w9HcPmDVLa6WF/diV6rpizDekwIbUxUpiZN5eEzH6bB1YBRYyTfmo9adXwLM+Qlm/n8wjzm5jnwhSKUpFmoyHWwq8nJrmYnKpWK6ZlWpmYc3fWo1xtkd0sv7S4/+cnKtVqrFg7NaDDVMZWHznhInM/HOUd0QmRZXgkgSdIdsix/b+BrkiTdAaxMeKCCH1ghy7JLkiQt8JEkSa/LsrzqoH4fyrJ8/iBtHzPyU8wczSbhu7taufXZjfhDSgG206elc/q0dF7Z2Mjza+sAUEnwx8vn8Nk5OdHjdjY5ueax1bS7AgBMy7Tx4NXzKEg1j/hnGS20Ki1THFPG2wzBSLB/JWTOBJWaCDLN7mbShlOoMAK7OrTckOok6O3ERwEAEpISkuVpI886+G348kwrn1S2CydkBEky60g6qNDqp5XtfOXp9Ti9yq5TRa6d65YU0NDt49nVO2nqqzxdmGLisWsXUpxuGXO7jxfsejt2vQhzPcDW+m5+8MpWtvYJKNiMGh68ej7feH4TrX35TEWpZu69fA4VeY7DjuXyhbj/vX08/EEVoFyr/3TlPM6dFR+GKBgZxPksGIyLf0aCtnMOd4CscCD+Qtv3OCYT2+u7PPz6tV1RBwTg7Z2tGLTqqAMCEJHhR69so7bDDUA4IvPkp9VRBwRgZ7OTD0W8u2C8qHwPMpRQrA5vB3q1DoN66Dtzuzt1pJnC6I06tN7umNcc+qQhJ9eWZ9r4tFKoM40mLn+Qh1ZWRR0QgC31PYTCSs2QAw4IQHWHhzd3DE1oQCAYChtqu6MOCECKWc8/NzZEHRCA/e1u3j+K4qZ7WpxRBwSUa/X3X95KfZdnZI0WCARRjiYn5GZJkrYCZZIkbRnw2A9sOYrj1ZIkbQJagbdkWV6doNuJkiRtliTpdUmSEgYFSpJ0oyRJ6yRJWtfWNvEUQXq9Qfa3u+PaO93xUoG9/hA9XqXdHwqzsbY7rs+OpmNf2vdYYKKfl4NGlmHfO5A9D4BGV+OwlbG2tOoosocI6yxoPbFOg11no22IeSElGRb2tLhEXsghGIlzs9sdYE9LvGqWNxiksi1emWhjrZBNFhyekZwzazpir7m5ScaEKpWJlN8OZuBC4AF6vMHotVogEIw8R7MT8ixwAfBq3/8PPObLsnz1kQ6WZTksy/IcIBdYJEnSzIO6bAAKZFmeDdwP/PMQ4zwsy/ICWZYXpKVNvPCLTLuRk4rjQ1Zyk4zoDoopzU82ktVX4Muk08SEZh0gkdKWYOIx0c/LQdO+B+Qw2JWK9w2uBpIHWdH8YLa16yiwBwnpLWg8sTKvdr2dFk/zkMbVa9QUpSp5IYJ4RuLczLQZOa08Pa7dZtAyLz9eGeusmceVgKJgCIzknDkrNzaUZ1tDD8sThGcuS6D8djD5yaZogvsBitPMZCZQwxQIBCPD0TghasAJ3Ar0DnggSdJR353IstwNvA+cfVC780DIlizLrwFaSZIm3R14klnHt88qZXbfpGjVa/jx+dP4YHcr3zunjFSLEmddnGbm/ivmkTqgcusFs7O4cG42kgRatcRtpxazWKjOCMaDPW9AznyQlItxvauOlGHkg0Rk2NWho8AWJKy3ovN0x7xuNzhocQ9dG7480ypCskYRjUbF5YvyOaXvxk6vUXHrqcV4gxGcviAXVGShkhS1rBuWForFE8GYMi8viVtOKUbfJ/QyO8/BKWXpfGZ2NioJNCqJa04oYEnxkdX9SjKs/OXq+ST35USVZli45/I5pCRQwxQIBCPD0ahjrUfJ45CAfKCr798OoBYoOtSBkiSlAUFZlrslSTICpwN3HNQnE2iRZVmWJGkRimM0Ye4quj0BdjY5aXcFKEgxUZZhRa9Vs7PJyc4mJ+GIzLRMKzNzHUzPtvObC2fR7vJj0qnRqlVY9RoybAYeuHIedV0eClLMURnf3c1OdjQ5CYVlblw2hVtOnYpakpQVmaNV5Oiph+ZtEPZD+nRILUGWZfZ272V/z35MGhNJhiTqeutIMaRQllQm6ncIDs3u16D49OjTBlcjxTnFQx6u1qnBrI1g1cmEVFY0vu6Y1x26ocv0AkzLsvGfLY1DPl5wZGbm2Ln383PY1+ZClsEXCqGWVKhVEkkmHVefkI83EMGsV7O5vpuyDCsatcSupl6C4QilGVampB0DyerOBmWuDfogvRzS4usjHQ3uoJs9XXtodjeTac6k0FpInauOBlcD6cZ0SpNLseqEuuDRUJBq5txZmZRlWvGHIkxJNTGvIIlUs47PL8xDkqAgSanttWZ/B5VtLqwGLTOy7RQdJPyiVkmcMT2DGdkn0eMNkmEzRB2SSYO/F1q2QU8jOHIhfSbox17gpsXdwu6u3fhCPoodxRQ7iql11rK3ay8qlYpSRyk51vgIEMHxx9GoYxUBSJL0IPBq324FkiSdg+JUHI4s4G+SJKlRnIsXZVn+jyRJN/WN/SBwCXCzJEkhwAt8fqJUZXd6A9z1xm6eXt1fEfyey+dQlGrilmc20tDtBSDJpOWRL8ynzRXgq89uJNth5ILZ2Tzw3r7ocZcuyGV/m5t1NV3ceUkF5ZlWbn12I7WdStKbzajhkWsWsHjKIOoxdFTB81dCW1/lUb0NvvAq69VhvvLWVwhElBjXWamzKE8u5+97/s6lpZdy+/zbxUVOEI+3C5q3wLJvASjKWK7mYe2E7OrUkW9TcjYiah3IMqqgl4hWCUd06O10+TuJyGFU0uDlGQ/khXgCIUy6o1lTEQwFu0lHMBThy0+u567LZvO9lzbR7VFi5XOTjPzfOeX838tbuWJxPjsbnby6uZHKNiVe32bQ8MyXFjMr1zGOn2CYdO6HF65WbvAAdBb4wr8gd8GghgmEAzy36znu3XBvtO3m2TfzTu077OnaA8D1M67nptk3YdIe+4Vuh8v6mk6+/9JW9rQq+UlmnZq/XD2f7zy/kZa+87Msw8q3zirl1mc2EAwrtxaLipL5zYUzmZoefx3MdhjJnoxS00E/rH4Y3h1Q4eDMX8Gim0AzdjW7GlwNfPO9b7KjcwcARo2R+0+9n+99+D06fMr6cqY5kwdPf5Bix9AXuATHBoNRx1p4wAEBkGX5dWD54Q6QZXmLLMtzZVmukGV55oH6H7IsP9jngCDL8p9kWZ4hy/JsWZZPkGX5k6F8kNFgd4srxgEBeOyjKt7d1RZ1QAC6PEG2N/bym9d2EorInF+RxaMfVsUc9/d19SzrC2m4843dfFzZEXVAAJzeEE+tqsEfHESSbfUH/Q4IgN9Jb/VK7lx7Z9QBAdjavpUMU4Zix56/s7dr79G/h+D4Yc8bkDUHNEoMdIe3HaPWgEE99HCEne1acqx957QkETLa0Hj6czg0Kg1mrYUu39DyOgbWCxGMHl5/iL9+XM0JU5J5fWtT1AEBqO/ysqe5F61aot3lR5KkqAMC4PSFeOyj/YTCkURDTw5qPul3QAACLvjgbgj5D31MAvb37Of+jffHtD285WFW5K+IPn98++NUdlcOy9zjhc11PVEHBMAdCPPIB1Xcf828aNsl83O54/XdUQcEYM3+TrY1HGPiLx174b1fxba9/VOlfQzZ1Lop6oAAeENeHtryEKVJpdG2Zncz79S+M6Z2CSYmg3FC2iVJ+pEkSYWSJBVIkvRDJlDY1GjQ5Y5Xy8iwGahsjVeFCUUi1HcpjolKJcVI9Ub79F2EjTo1+xMoy1S2ufAGw0dvYMe+uCZPJEi1szqu3Rf2oZKUP3e3v/vo30Nw/LD9FchdFH3aMALKWLs7deRZ+x3rsM6CzhvrMDj0dlq9Q88LKcuw8sm+Y3oqGndcgRCVbW5KM6wxDsYB9rd7mJpupb7TQzCBs7G90YlvMHPbRKOrOr6tdTsE4r+Lw9Hj7yEix34/YTnMwZv/Pf6ewVp4XDJwMfAA+zvcGLT9u6KZdj21nfF/py5P/PV9UuPtgoPOLSJhOCgEdrRpcjfFtdX01pBhzohp29Wxa6xMEkxgBuOEXAGkAa+gKFil97UdsxSmmuOUrTpcgYTF0ewGLaeWpfX18ZObFLuda9KpifRdZ3RqFUsSKGmdPSMTh2kQq86Fy+Kakk3pnFMUX77FrDUTkSNoVVryh1AYTnCM4++F6o8gb3G0abjKWIEwNLo0ZJljnRCNN1Yhy6Fz0OYZXl7IJ5Wirs5okmY1cPaMTF7b2sTp0+LVsk6Yksynle1U5DoShsVdMj8Xi2HsQkJGnPzF8W0VnwfT4H4fOZYcHHpHTFuyIRlPqH9X3KgxkmvNHYqVxx2zc+PzG8+akcmne/vr1Xywp53TEpyzB+eETHoc+WA8SLHOnAb2vDE1Y2bqwQKocEb+GWxo2RDbVpio9JzgeOOonRBZljtlWf56X3jV3L5/dx75yMnL1DQLj1y7gGy7Ep4yL9/Bry+axYnFydy8vBiDVoVWLXHlojzm5Dv4+mmlLClO4eUNDXzl5ClMz1LiTfOTjXz/nHKeX1PL7Fw7f7x8DvMLk/jaiqkYtWo0KolL5+dy9sxBVmbNWwxn/hp0ZlCpYd51aKecyvUzr+f0/NORkLDpbHx93td5p/YdMkwZ3LfiPlHZXBDP7v9BxgzQ9ycQN7jqSTEMPR9kf4+WdHMI7YBUj5DegvYgmV6b3karZ+hF7kozrOxpceES9UJGlQtmZzG3IIkUi47LFuSiUUkYtCpuWj6FLk+Ai+fnUtPhxmJQ872zyzHp1KhVElctzuf8iuzxNn945CyCc34PeitIKphzFcy9avDDWHO4b8V9FNkVPZdiezF3LLuDHe1K+EquJZf7V9xPob1wJK0/ZinPtPKdM8uw6DWoJDi/IovzZmXS6g6hVSvnZ16yiZuXF0cXD5NMWn79uZkJJaYnNUkFcMXzkFKiPE+bBp9/Fhxj7ISkzORHJ/wIi9aCSlJx/pTzubj0Ylbkr0Cj0qBX67l59s0sylx05MEExzzSkXLAJUm6R5blb0iS9G8SVDuXZfkzo2XcoViwYIG8bt26MXu/VqePXl+IdKseq1FZzQuFIuxp7SUiyxSnWzBqNQTDEbbUd7O3xYXNqCHXYaLD7cdh1JFq1REIyaRaddiNiuJGJBJhV7OLsBxhaqoFo34IibWyDN21EAmCPR80yti+kI9mdzNqJDy+blr8HVhUBoqsuSTZD70Tsq19G7s7dyNJEmVJZcxITVg78nhCOnIXhbE+L0eUpy+GzAoo7o9N/+knP2V57nKyLUO7gfxPpYm1TXouKu0PhTC178XgbKZh0fXRth2dO2h0NXHrnFuHbP6vX9vBt84s49Sy+BXPY5SjPi9h5M7NnY09bGt0oteoyE02oVGBSavG5Q/T6vTjDoaZlWOjOM1CfZeXUEQm12FEqxnMpvsEprsWwkGljo67XRFy8PcqSlkZs0B1dJ+zy9dFt7+bJH0SDoMDp99Ji6eFVncrtb21pBhTmJE8gxxbDsFIkD2de6jqqcKut1OeXE66aUKf52M6Z9Z3eVhX3YU/FKY808rsvCSC4QgNXV5UEuQmmVCpJHo8AWo6PBh1akoyrLj9IXY0Oqnr8pBhMzAj24bDNMnUsA7G1wNtu8HbrezSpZaCwTZiw7sCLnZ37abB1UCGKYPy5HLs+sRqm42uRgLhAFnmLPQaPaFIiEZXI5IkkWPJIRQOsbl9M1XdVZi1ZqalTBvtRPVBzZmCseFo7nqf6vv/XaNpyEQm3WYg/aDfsUajYnp27I9v5Z42bnxyXTTsal6+g6npVl5cV8e1JxbwnbPKsRj6v3KVSsX07GFOEJKkrIAchEFjoNBeyMvbn+Kn634fbT8/7zT+b+F3sVvjbyzXt6zna+9+DWdASdhLNiRzzyn3MDdj7vBsFExs3B1QuxoW3RhtiiDT7G4ZljLW3k4tmebYPICQ3orGuzOmzaFLYpNn85DfB2Bapo1P9nUcT07ImLOxtosrH1kdzVvLSzLytxsWEQhF+OLf1tHRl0NnN2p59suLmZF9DEqBO/oWcLrr4MUvQGNfiIlKA1e/BFNOOaphkgxJJBn6V+ItWgv/bPwnd667M9p2ZsGZfGfhd9jduZuvvfe1aC7JooxF/Pbk3050R2RMqG5388Un1lLZrix06DUqnvnSYhYUJlN4ULiV3aSjos/JCEdkXlhbyy/+0z8XJbpGTyqCXvj4PvhwwK3aKT+Apd8A7fBrnQTDQV7Y/QL3bLgn2nbt9Gu5Zc4tCZXcDl680qg05Nv6F0A/bPyQb7//bUKysoNdnlTOb5b9hpKkkmHbKpg8HHHZRpbl9X3/VANrZVleOfAxuuZNHtp7/fzkn9uiDgjAhtpucvpyQ/72aQ17W3vH1Ka6th3cselPMW3/qXuHvZ2JE8JerXw16oAAdPo6eav2rVG1UTAB2P6yIjU64ELS7m3DqDWiVw99ZXBft5ZsS2yIVFhvQ+vtjmlzGOzDqhUCMD3bxkf72oY1huDQBEJhHlpZFSOcUdfl5eN97byxvTnqgAD0eIO8tL5+PMwcOxo39DsgAJEQvPFDZQV6COzu2s2fDpqr36x5k12du/jV6l/FJLOvaVnDzs6dBw9xXLKmujPqgAD4QxHue2cf3sDhRRCq29387vXdMW3jcY0eUdr3wkd3x7at/F1CAZuhUOOs4U8bY8/Rv+34G/t79g96rBZ3C/dvvD/qgADs6trFzg5xXh9vDGaP/DpgkyRJn0qS9HtJki6QJOkYC6ocOp5gmGanL659oCyl0ze2MeueoDsm4TFqRwLllVAkRK2zNq49UZvgGGPjU3EruI2uRtKGsQsSjkBdr5asg3ZCwlojqpBfCWnpw6gxIssR3MF4xbijZWqahZoOD93HmuLNBMEfirAvgaJfTYeHxp54haKdTceY/OnBeBKkQ3bXDFot6wC9gV68ofjvscffQ6snXjnO6T/Gv9+jpDGBOlZV+5FVJl3+EIEEKm5ObzBB70mCr0cJzx6IHIERUlpzBV0xTsMBBi5cDmasJle8ipZQ7jz+GExi+hdkWS4FLgbqgQcAsfTYR4ZNH5d8qZKUOgYAVr2GguSxLT6VZctjZtK0mDa9Wk+BLb7IvUal4cyCM+PaT807ddTsE0wAWneBs1GpDzKA4SpjNbg02HVh9JqDLoqSREhvjZHplZBIMiTR6hn6dKJRq5iWZePTSiHVOxpYDVouXxCf4HpSSSrLpsarBV4yf2yTYcec9GnxbRVXgCUjvv0oKLAVxNRRADCoDRTaCjmr4KyYdpWkiia2H+8sLIyfoy5fkHfESue5SUaK02LDtax6DQUpk1gxK6kQzActHFmzlPYRIMeSQ7Y59h7HrreTZx38bz3XksuZhfH3G+K8Pv44aidEkqSrJUl6CPgHSqX0PwHxGrHHKXqNmttPL+Ezs7NRSZBtN/DTC2bw8oZ6pmVZefz6hXExqqONzZLJLxb/gKUZCwEoshby52W/Z0p6RcL+S3KW8MWZX8SoMWLWmrl59s2ckHXCWJosGGs2PgVFyxV1tQHU9Q5XGUtDliXxamTIYEVz0EqyQ++gbRi1QkDJC/lgr1gXGS3On53FV06egl6jwm7U8psLZzI/P4klU1P4/jnlWPQaTDo13z6zlOVlw6svM+HJmgOXPgHWTOW3M+dqOPEWUA8tnyDDnMGPT/gxCzP75mpbEXctv4vZ6bO5dc6tnFN4DipJRaY5k3tPvZey5LKR+yyTmDl5Dn5/SQVJJi06tYovnlTIRfOOLG+cYtFz/xVzOXGK4sRMy7Ly13G4Ro8ojjy44kXI7ivUmLsIPv8c2EZGmS7NlMYfT/0j89KV8aenTOeBFQ8MSU5ar9FzVflVnFN0DmpJTZoxjV8s+QXzMuYd+WDBMcUR1bGiHSWpHagEHgTek2W5ehTtOiyjoULkC4bZ3tDDvlYXSWYds3LtZNmNtDp9bG3oobXXT6bNgD8UpqnHR0m6hfkFSRgHaOL7g2H2tvbS4QqgU6vITjIAEg6jFvtIqm701EPjRqU4UVo5ZM4+bOKZ19dNh6sJSaVmf3clLe5W0q05aDRGmjwtFDmKmJY8DYPGQCQSoaqnCkmSCEVC7OzYiUFjIMOcwf7u/STrbUxXmUlv3aNMellzwZREnbOOHZ078Aa9lCSVUJ5cjvqgG9tJyrGrjhUOwh+mwem/iJNx/PHHP+HUvFOGrIz1+FYrHV41ZxTGhwMmV63ElTGdnoITo20r61eSZc7mguILhvR+ADUdbv703j4++t6KI3ee/Iy6OlY4IrO9oYfqDjdmvYZOV4Bsh4FAWEarlshPNivzZmMPkgRT0iykWvRk2Q1I0jEoRNNRBU2blATgzJlgTIXOSkUcpLcZQj5lPs6aDRodbZ42dnTsoN3bToGtgDxrHnu79tLiaSHHmsP05OnY9P3CJO6gm1pnLZ6gB61KS4Y5g0ZXI1U9VRg0BowaI8FIkIrUCrIsg5RzH1vGdM7cVNtFpzuALIPNqGFmpg2j8ehq0rh8QTrdAewjfY0eaSIRaNkKzdtAa1ScYFsWNG5SKqKbUiF7juJweHvA1wXG5EMqY9W0bWNHxw4C4SBlSSWUZS5AOkjZLRAOsKNjB1XdVdgNdmYkzyDTkokr4KLb341Nb8OmSzz+1rat7OrchT/sZ4p9CgsyF6BLkF/oDXqp7a3FoDFQYIsX2BlhjsFJafJz1Ms2siynSpI0AzgZ+LUkSSXAblmWrxk168aQN7c387XnN0WfLypM5s5LK/jt6zv537b+GgY3Ly/mP1sbaejy8qcr5nLugBCsd3e3cvPT/cmKc/Ic/OXqeSPsgDTA36+H+jX9bZc9BdMPrZRsNDhIioT54/q7eaHq39H2S0svZVv7NnZ27uSOk+/g3KJzUalUTE2ayqeNn3Lz2zcTlvuUcKx5nJZ/Gj/d/gTL0ubxS7+OlH+/CEu+Tu2i67n53duo7VXyRzSShgfPeJDFWQkKfAkmDvveBnN6nAMSliO0eoanjFXVraUsOXF+RlhnQes+eCckaVi1QgDykk24/CHqOj3kjXHo47HIp5Xt3PC3dfzf2eV8+x+b+b+zp3HD39bhDymx9BlWPdecWMBdb+4BFFWs5768mGyH8XDDTk7a98JTF0JPnfJcrVXqhrTsgNpPoGW70i5JcPkzdBUu4VerfsW7de8CcELWCWSYMvhX5b+iQ94y5xa+NPNLaNVaInKEf+77J79b8ztAUSb84swvxqhlVaRWMMUxhSe3P8ndp9xNpjlzbD77BGbt/g6+/vwmGnuUfEytWuIvV8/n9GlHFxZnMWgnRxHNuk/hyc/259Jlz4MF18OrX+3vU3QKXPwIWNLBeGhluqqWzXz5/W/Q6lPEQHQqHY+ecg9z82IDW1bWr+Sb738z+rwirYK7lyvnnUVn4VBsbt3M9z78Hg2uBkC5H7j7lLtZkR+/OGTUGsWu3nHOYMKxbEA+UAAUAnYgPrNrEtLc4+Xn/94R07amupOdTc4YBwTgiU+qOW9WFhEZ7n5rD809ykpvW6+Pn726PabvprputjeMcAJh85ZYBwTg9e+C6/ChLPs7d8c4IAAv732Z5XnLAbhjzR20uJXP2hvo5d4N90YdEIC63jqMGiMqScWHbRvYm91XP2T1n9nUsj7qgACE5BD3bbwPd3BoSZqCMWLDU1Acn/PT7m3HpDUPSxmrxqkh05xYiCGkt6L1xOZuOPR2mofphKgkiYocOx/uFdXTh0uvN8jv/7ebE4qS+e/WJmbnOnh3V2vUAQFo6fXT4w1h7atv1OMN8t+t8cmmxwQ1H/c7IKDcDG55EZKL+h0QUBKDX/8e+zp2Rh0QgPkZ82McEICHNj9EjbMGUObXe9bfE33t7MKzeWTrIzH9t7RvIceSw5b2Lew6hMLh8cbGuu6oAwIQDMs8tLKS5u74HdhJS8AL798RI+ZB/mJ46yex/fa/r+yUHIHVzaujDghAIBLg0Z1P4vf3C0+0e9v57erfxhy3pe3ozrut7VujDggo9wOPbX0socCCQDAYdayPgAuALcDlsiyXybJ87eiYNbb4ghE6E6jq9CZQs/IGw2jVytfW4vTj9keiY7S7Eo0xwmobiVRR3K1KiMBhcAXipQfDcpgD4Xhdvi78YT8AvrBS6PBgvCEvWpWyauQ6IBmp1tPli1eKaXY34w/5D2uTYBxxd8D+D6AwPq2rwdVA6jB2QbwhiW6fmhRj4jUKxQk5aCfEkETbMBLTDzAj2857u8XFbrh4g2Eae7ykWPS0OH0km5X/H0yXJxBTV6G6/Ri6+RuIM4Fz1dsce2N4AFdz3HwbisRfS8JyOKpe6A158YX7v1+LzkLPIVQMQVkoEijS+AfT7PTR6z+8OtakIuRTimQORGdRwrEP5ihU05rc8Ys99Z5WgqH+888X8tGZ4LruChxZwbDLF29Xi6cFT+AYnRsEw2Iw6lgVsizfIsvys7Isx4nAS5J0/8iaNnZk2Q2cOzN2a1urlihOs2DSxeY1zM1zsKdFuQB8dk52VPEqw6bnork5MX3VKomSDOvIGptWrhTGGkjF5xUVjMOQby8kxZAS05ZnzYvWZziz8EwyTMoWdqohlUtKL4kbw6F34A/70av1FIb6JnljEjPTZsX1vbT0UpKNQ1dXEowy215SaoPo4hMxG4epjFXr1JBuDqE6RASuoo7VHdNm1Vnwhjz4w/E3uoOhItfOqqqOGGlsweBJs+q5clE+H+9r5/RpGazZ38EpCQpBFqeZaRqwEv2Z2SOTBDvhKFwa31Z2NkjqOFEH5lxNgWMqRk1/WJov7Iv7TRXZisi1KEm9OeYcZqfNjr62oWUDS3Ni31Oj0qBRaVBL6tGuLD1pmJsfXyXgs7OzR/66O56YkpTQq4HUr4XSWNU01DqlQvoRODEzPkz68sLzsAxQ1sowZXD+lPNjh5fUTHFMOeL4M1JnxLWdW3QuhY7CIx4rOP4YzE7IkUgwS08O9Fo13zmrnMsX5mLQqijPtPLE9YuYk+fgyRsWMTvPjl6j4uyZmXx2TjYf72vnykV5XH1CARqN8hXqNGpuWzGVKxfnY9CqKEm38Ph1C5mWNcyK6AeTMROufFFxRrRGmH8DnPxt0Bw+dCY7pYwHlt3B4tS52HV2lmYv5YYZN/Bm9ZtcOPVCvjb3a+g1SnK7JElcXHIx18+4HpPGRK4llx+d8CNWNaxiZvIMHpz3Paau/RtMWQGff5aZ6fP44yl/JMeSg1lr5oszv8jnpn5uZD+3YGTZ9PQhqzvX9dYNq0ZITY+GDNOhVyLDOjOqoDdmFVmFCoc+iTbv8HZDHCYdaRY9m+q6hzXO8Y4kSVy+MJ8L5+UQDkc4vyIbly/I9UsKsRk0ZNoM3H3pbLLtBtKtOrLsen71uRmcMCXlyINPRnIWwKV/A3su6G1w8neh9Bwlr+qs30JKiVLsc8GXYOk3mJJUzIOnP8is1FnYdDZ6/D3cvfxuFmQsQKfScXLuydy9/O7oQo1Vb+WXS37JWQVnoVPpCIQD3FhxIxdOvRCD2kCJo4Rvz/82qxtX88BpD1CWJOLoAWbn2vntRbPIcRix6jV88aRCzpg+NJnkCc2sS5VzzpyuSO7OuxbO+CXMvgJsOZA9F65+ObF09EHMzlzIbxf9iGxzNin6FG6dfh1nFJwe00er1vKViq9waemlGNQGih3F/Pm0Px/VeTc3bS6/WPILss3ZmLVmriy/knOKzhnqJxcc4xy1OtYRB5KkDbIsj4m+2mipEAVDEdpcfsw6dTSZvKnHS1WrC08gTIpFR7JZT0SO4A/KbK7vxmpQY9Zr2d7oxKhVMzvXTo7DiEGnxjGaahueLgi6FV169dEl1rV72tnctokaZw3F9mJKk8uQJIkUQwravjF21X/Clo4dqFQq5qXNwWzNIRjysbd7H7u69pBuSmN2UjlTdQ4wJsWspHf5ugiEA6SZ0lBJI+nfjivHnjpW+z7465lw8V/jV3GBH338Y07LP42sISa+PrzZhicocWr+oUMEszY+T/2JNxKw9K+uv7LvFc4sOJN5GfOH9L4HeH5tLbkOI985u3xY40xwRl0dCyASkWlx+tBrVHR5Ahi0KiSgscfPlvoeIrJMWYaV1l4vM7IdlI/0ostEoHWXsvIc9kPGLLDngy0TOvdD3SolLCazQkkI7qpWKlRnzqY5pYDNHTtocDdQllRGRVoFKklFi6eFmp4a9jv3k2HKwKK14Al5aHY3k2fNo8heRLopHavOSjAcpMPXgU6tOCZGtRG74dBJxxOEUZszt9Z3K2qVTj+lmVbm5Nnp8QTwhWRkWcaokZiSZkWvG5pU8oQlElYUMevXKtfc/BPAkKycfy3blEiI3AWQEb8LkYiq7io2tqzHF/ZRkTaHGakzEl6zg5EgHd6O6HnX5etiW/s2qnqqyLfmMyt1Fqmm+AWrmp4aapw1hOQQGaYMypLL2Nu1l23t21BJKmalzqI0+ci7NiOMUMeagBxjv9ThodWoYpRdOlx+/u8fW1g5INH1B+eUc1JJKp9/eBWeQIj7rpjHl/62jlBEceaSzTr+cvU8FheN8oqgKQk4+oL1roCLezbcE5Mced2M67h1zq1RB2Rr3YfcsPKb0dhkk8bEUyv+zAdtG7h3433R42anzuY3J/6UfF2sPniS4ejtEYwjW15UckESOCBhOUybp5VUw9DP3+oeDTNTD1+5/ECtkIFOiF1nH5HkxYpcBy+trzvWnZAxQaWSyOqbE5Mtyk7pe7ta+cpT66MVp21GDXdcVMHFf/mEF75yIjNzJvxN8tHTsgP+dl5/hXS1Fr7wKoR98PTF0FWltEsSnPU7ePcXEHDTMedyfmoI80lLv4jIt+Z/i0tLL+WZHc/w4p4XAShNKmVR5iKe3vl0tN+ZBWfy0xN/Cigr0kIFS2FXk5Mf/XMbm+v7c2V+cG45n+xr5/09yjVarZJ48Op5nDH9GPvOqj+Gpz+nOCOgOL2zr4A3vt/fJ2sOXPwYpE497FD7uvZxwxs30OVXcjc0koZHznyEBZkL4vpqVf3nnz/k56/b/soT25+Ivn7BlAv4weIfxKhlVfdU86U3v0RLn9CISlJxzyn38P2Pvh8VqzFrzfz1rL8yPWX6IL8IwbHGSC5XH3Ne5u7m3hgHBOCpVTW8tq0Zpy/ENScW8tSn1VEHBKDTHWDVBKzaXNVTFafO8uSOJ6PqLAAvVf07JjnSE/Kw193IwweptGxu38yu7n2ja7BgdJBl2Pb3hAnpAK2eViw6a9QxHQp1Tg0ZpsTKWAcI620Jk9MTCSIMltIMCzWdHtoSJK0KhofbF+DZ1bVRBwTA6Q2xsa6bvCQT/97SOI7WjQKV7/Q7IKCEEH58HzRs6HdAQPldrX0Yys8DYF/W9BgHBOCBTQ+wr3tf1AEBODXvVJ7b9VxMvzdr3qSyu3LkP8skZ1ezM8YBAbj/nX18dkAuZjgi85f3K+nyHEO//YAb3v9tvwMCUHSy0jaQpk3QvPmIw61qWhV1QEBRr3p066NRYZpDUe2s5skdT8a0/bvq31T1VMW0bWzdGHVAACJyhAc3P8iizEXRNnfQzRvVbxzRVsGxz0g6IfeO4FgTAk8wPq5dp1HT0peImWrR0+GOX/FN1Dbe+ELxCb8RORJ1OuRwmEZfvPPkDfvwhuLDag6ouggmGS3bFCW1QyQwNroah5UP4gtJdPvVJB1CGesAIZ0F3UEyvUl6x7BlegE0KhUVuQ4+2COqp480wbBMuyv+ZqWt10+GTU9j1+FV+iYdrgTnY28jJFKncneAwQGAV44//31hX9yNnoQUI4V+gERz7vGONxj/nboCoaha5QE63AG8gWNIHSscBNdBizNaQ+Jz8CgUqDq88df5Fk8LofDhF458YR+RBOf1wedqIlW3Ln9XXGHD5oM/k+C45IhOiCRJ/5Yk6dVDPQ70k2X5iVG1dBwoTrNENfAPkGM3cM4sRYnq+TW1XHiQIhbAkuKJl5yZb8sn3RSrblPiKCHPohSqk9RqLik4O/44YwYnZZ8U02bUGJliKxw1WwWjyLZXoGCpEj6SgPre+mEpY9X1akg3hVEfYV80ZLCic8XuMjoMSbR5R0Zed1aOnbd3Dt+hEcTiMOv5XII5b1lJKh9Wtid8bVIz9Yz4toVfUnJDDg5nnPE5JVEdKAz4sWhjC7otyV5CnjUvqogFUNNbQ3lybNhgsiGZAvuoV4+edExNs2DUxn7np5Wns7Y6dkf1knm5ZDuOoWKlRgcs+kpsW82nUH5BbJvWCGlHThw/MfvEuLYry6/EnEApcSB5ljxKHCUxbemm9LhK57PTZyMdFBhzUclFfNL4SUzbuVPOPaKtgmOfo8kJuWvUrZigFKWaeepLi7j7jT1sa+zhnJlZfGlZEek2A/d9fg4PrqzEptdy++klPLemDrNezc2nFLOgcOLlRmSaM3ngtAf4y6a/sKF1A0uzl/LlWV+OkdFdnLGIn8//Nk9X/gtJkrhu6sVMdxTz1dk3k2pMZWX9SgpthdxUcSMVmcNLHhaMEzv/BYtvOuTLda46ssxDl1mtc2pIP0IoFkDIYEPbElvc06az0RvoJRAOoBtGoUSAOXkOnl9TSygcQaM+ZkQSJgRLpyTzo/PK+etH1ei1ar54UhF7mnu5+5LZLC46xmS5cxfCZU/Ch39Q6jUsvglKz1MqUl/9T3jzR+BqgoU3QvEK6KgEtZbCEDy84n7+vPUx6l31LMlewjXTryHLksW9p97Lg1seZG3zWnxBH7fOuZX/VP6H1c2rqUit4Na5t5JjOcacuRFgYVEyf7l6Hve9u5fqdg+nT0vnikX51HZ62FDThS8U4dyZWZxXcXi5+knJjAshHICd/1Gc3xNvA3u24qDs+i+kTIXl34O8RUccqiKtgntOuYcntz9JRI5wZtGZnJofX7T2YJKNyfz+5N/z6NZH+bjxY+alz+PmOTfH5SzNTJnJn1b8iQe3PIgn6OGC4gs4o+AM0oxpPLzlYdQqNbfMuYX5wxQgERwbHNEJkWV55VAHlyTJAHwA6Pve6x+yLP/0oD4SSijXuYAHuE6W5Q1Dfc/BEAhF2FLfzeqqTvJSjBi1arY19JCbZGJRUTIFKWbm5CXx0Bfm4/KFSDLrolu/mXYD51Vk0+b2s7AgiVPL0gAlJ+SpT2vJcRhZVJRMYephVheat0H1RxDyQsFJkDMPvD1Q9ynUrlKSz1RqaN2phM/knwCOPGrbtrO+ZR1NnlamZ8zFE/TR6GlmenIZ9V1VBEJeFmTMozw7dkIqTy7njpPvoDfQS4u7hU8aP+HlvS8zK20Ws1RWstsqKcss4fzCs1BJatLthbxc9w56jZ4bZ93IF6dfg01nJ9miSCDW99azoXUDTb1NzMmYQ1VPFb2BXuZnzGdW6qxD3ki2e9rZ1LaJnZ07mZ8+n1ZvKw29DVSkVVCRVoFdfwwltk4k2veCr+ewWvINrgYqBtQrGCy1Ts0hixQOJGSwoTkoJ0QtHZDpbSXHknuII4+OJJOONKueDbXdLDrWboxHGW8gxKa6btbs7yTNqueEKSl0ugNsb+ghzWpgd4sTvVbNvZ+fi8WgoqHbR7JZR2GKCYth6LlE44osK+pDDesVxcH2PRAJQcESSCmFuVeDOQ2cjVC9UileGHTDWb+hxprC+s6dNLZ9ytTlt9Lt7aRA5yDL3cm5+adR6apnin0KH9R9gN1gZ3babH570m+pc9bR7munyd3ERSUXcWPFjeTb8unx9/C//f9ja/tWsi3ZFNoKafe2MzdtLs2eZta3rCfdlM78jPkU2gsTfBSZ7R3bWde8DpWkYmHmQqalHFm6dTKQZtVz++mlhCMyerVErsNAMBzh/NnZuHwh5uTZSTZr2VzXzaqqDrRqFYunJDMjewJfUzr2Qc0nyjlVcCLkzFec2eqPlFCswqWKJH/6dEWJTW8DU4qijlV2HuSdoMhDGxy0elrZ3LqZXV27KE8uZ27aXFJ9TmXnpLsG8k/AkLsQq87K0tyleENeCqwF6FTx12pP0MOWti1saN1AljmL+RnzkZE5o+AMFmctVnb6ItDQ28CG1g3UOGuYkzZHuYYb7JxVeBY9/h5Kk0pJNaZycenFrMhfgSRJOPSOsf+eBROSo1bHkiSpBPgtMB0wHGiXZflw1Wv8wApZll2SJGmBjyRJel2W5VUD+pwDlPQ9FgN/6fv/qLOqqoNrH19DulXPxfNy+fP7/cmApRkWnrh+EdkOIyadBtMAyb9PK9v54t/W4emLO9WoJP505Vx2NvVy7zt7o/2KUs08ecMi8pITbA03bYEnzgV/X1ynSg3XvaY4HP/5hlIPxO+E9U/0H1N0Cg3n/oZbP/gO1a46pW3nk9xUcRN/3/N3uvxdfGv+t/jD1gfR7dDx+Kn3MyM79qs0aAxU9VTxg49+wH7n/r4x4Pb5t7M4o5Rr3ruNYESp32BQG7hlzi38atWvSDGk8PjZj0cdkBZ3C998/5vs7NzJTbNv4nsffI+OATklf1rxJ5bnLY/72N6glz9t+hMv7X2Ji0ou4o8b/siuzl3R178x7xtcP/P6Y0nid+Kw6zVlpewQ320wEqLd2zGscKwap4ZCe4Iq0gcRUeuRZBlV0ENE2//7SDYk0eJuGbYTAjA718HbO1uEEzJI3t3Vyq3PbgSUoq0/OHcav/rvDn5w7jRue24DB3Q4bAYNNy0v5vdv7AbAoFXxwo0nMjvPMU6WD4P6NfDE+XDaT+DlLyu7HqAUgDvjl+Dvgfd+rYRiffQHcCv5RvXLbufm7jXUHZiPgVvn3Mo+5352duxkS/uWaPsV5Vewas8qTsw6kZtm3cTj2x/n1apoRDPLc5fzkxN+wj/2/oMHNz8YbS9LKuOqaVfxTt07/GH9H6Lt2ZZsHjnjEfJt+TEfZXPbZq5/4/podXWD2sDjZz/OzNSZI/d9jQP7Wnv55gub2N3SX7X7b9cv5OsvbKLbo8w5kgSPXLOAm55eHxWMMenUvHDjCczKdYyH2YensxqeukhxEA7w2Qfgvd+As0F5rjHCRQ/B369VnGVQ5PEvuA9evCZ6mHvetfzRbuA/1a9H2y4q/hzfa+/AtOmZaNvqG9/g9ve/SW9QufdQSSr+sPwPnFZwWoxpb9S8wU8+/kn0eb41n+tnXs/PP/15tG1ZzjKW5SzjN2t+E2176PSH+P5H349WXJeQ+P3Jv+fsorOFgqYgjsHc6T2O4iCEgFOBJ4GnDneArHBgxtD2PQ4uTPJZ4Mm+vqsAhyRJo76f6vaHuOftPcgynF+RzdOramJe39PiYkejM+Gxb+9oiTogAKGIzMsbGlhfE7uyu7/dfcgx2PtWvwMCivJF3RpYeYfyvOxs2Ph07DH732dX155+B6SP53c/z1mFZxGRI7xd+zaLMhfhDXl5t/bdxG/dtbffAenj0S2PssPTFHVAQElE29u1l1xrLh2+Dra2bY2+tqdrDzs7d6JVaQlHwjEOCMD9G++nN0HiXLWzmpf2vgRApikzxgEB+Mvmv1DfW5/QbsEw2fUfpejaIWhyN5Gkd6CR4qV7j5YDOSFHRJIIGexxCll2nSNGWWU4zM138I7ICxkUnS4/v329/zd5cmkaL29oYHFRCm9sb2GAECBOX4h2lx+7Udn98AUj/HvzJFXHWvdXpRBh85Z+BwSUEJjaT5WV5oBLuQl09wse7LQlxzggAM/vep7SpNIYBwTgpT0vcVr+abyw+wX29uyNcUAAVtavpNpZzRPbnohp3921mxRDCs/uejamvdHVyM6OnXEf5YXdL0QdEFDm8f/t/99RfQ0Tme2NzhgHJNmkY0t9T9QBASUX7Pm1tTGKlZ5AmDe2T9B5oGlTrAMC8O4voeTM/udFy+Dje/sdEFB2RBrWxdTpqkotiHFAAF6u/CfV6cX9DXknsq5lXdQBAUWg5qkdT9Hu7c/Ra/W08od1fxg4FLW9tbR5YsU+Pmz4EKuuvzq9RWNhV+euqAMCICPz6NZHY8YXCA4wGCfEKMvyOygFDmtkWf4ZsOJIB0mSpJYkaRPQCrwly/Lqg7rkAANn8fq+toPHuVGSpHWSJK1raxu+6k0oHKGrb/LSa1S4E6hp+BKoYwF0euLVr7rcAVQJkn29hxgDT7xCBXJECZcBZbU6Eh9b7w/FK9O4g26MGkXL3xVwYepbWe4IxKtUAAml+DwhT0KVFlfQhVmjTHTukDtuDI1Kk3A8Z8BJMBy/Ij6wbyKlDX/YH+MITXRG+rwcNTyd0LJdCfE7BA2uBlKHoYwVjkCLW0Oq8eiUaUIGK1r3QQpZRgdNIyDTCzAlzUKnO0Bd5/Gp5DaUczMQlnF6+39/Zp0Gpy+IRa+JaT+AOxDGoO2/jLT2xqvwTXgiEehtBb21f/4diN+p3ACqNErBwgH4EsxhrqCLREWAA5EAGklDWA4TiCRWUAxFQgnnUxk54aKONxyrTBSRIwnVj9p9E+cGcKhzpv8gdSyzXo0rEDqoTRPjlBwgkaLbhCCBaiU+J+gHiBroreDrju8XcCs7dQeexq3vKvgHttuycCY4j3qDvTHX61AkhCvoiuuX6Jo98Fw2aAwJld0O5PoJBAczGCfEJ0mSCtgrSdJtkiRdCKQf6SBZlsOyLM8BcoFFkiQdvCecSEcn7tcky/LDsiwvkGV5QVpa2iDMTozdpOOLJxUB8MHeNs6ZGZtcZdSqKc20JjqUs2bEF0K6cF4OWXZDTJteo6I8K/EYlMUrUZEyFeZ9Qfl381YlHnkg5jSmOqagV+tjms8uPJsP6j8A4NT8U1ndpPh5Z+XFbq8eYIp9StRpOcC5ReeSb4j/XmenzWZv917UkpqZKf1/uin2KZi1ZrwhL8mG5LjwqWumXxOT9H6AfGs+pQ4lJyEsh+Nk+87IP4Nsy9ATo8eakT4vR43KdyGrAjT6Q3Zp6K0nxTB0J6TFo8ami6A7yo2UkN6GzhN7c5SkTx6RWiEAKklidp6D93aPjOLWZGMo52aGTc8NS4uizz/smxs/qezg9OkZcf2LUs20OPtv8C6aN/wwujFHpYKFNyhzbt4J8a8XLlPifEI+MCbHhDOWhImLpz+36Fx6g71xc9uJWSeypX0L89LmkWfJozQpNjcrx5JDliWLU/JOiWm3aq3RcQeiUWnixlBJKi4ruyzuI5w/5fzEn30cGOqcWZppwTJArbKuy8vcPEeM0N+Gmq6ECm3nT9Rk9fTpMY4EAAu+9WOA1wABAABJREFUCLsH7GhUvgvzro3tI0mQPVfZEekjv7edAmtsaF6po4SC7gG7k9tfjqnXcYALp15IlqX/O0o3pfP5ss/H9NGr9XH5mlnmLDRS/9+k3ddOeXJ53P3AJaWXTKrrumDskBKt2CTsKEkLgZ2AA/glYAd+f1B+x5HG+CnglmX5rgFtDwHvy7L8XN/z3cApsiw3HWqcBQsWyOvWrTvatz0kHS4//9vWzGMf7efSBbm4/CFe3dxISbqFr64oYW5+4vjFbref9/a08+iHVQRCEa4+oQCXP0gkAsFwhFc2NTAl1cJXV0xlQeEh4tGDXti/Et6/Q9nmX/oNKDsXXK1KMbmt/4ATboHOSiVEwJ4PJ94KWRVsrP+Ih7c/TrWrkfOKzkGr1vPfqv9yaekl1PbWsaV1E1+Zdg1LcpdjMCZOyPu44WOe2P4E9b31nJZ/GudknkBB1cd8kF7Io7ufR61S8fmyK/ik6VM6fB3cPPtmFmQsQD1AlnJr21Ye2foIvf5eLim7hBd3v0iHr4Oryq/izIIzSTElliqu7K7k2Z3PsqFlA1+u+DJvVL/B7q7dnFN0DheVXESeNW9Qf8dR5qiLcI7UeTkqvPRlJZmxr5haIv6w/o8U26dQlnxkmcdErG7S8/xOK9fNPEQI4kFYmrejDvlonnN5tM0ZcPL0jqe5d8V9Q7IhzqaqDtbWdPLMlxLcXE5uBlUcdjDnZnOPj1c3N/DMakVg45tnlLKruZcdDT1kOgz8a1MjZp2GG5dPQadWcfdbu1FLEl9dUcLJpWmY9Uedajhx8Dlh75uw5w3Imq2Ey8oRmH8tWLNh9YNKWEzVBzBlOWz9O7hbkZfezsbsMh7a+ldqXbWckX8GEhK2iMy8lOk8Xf1ftnXt4aSck8gwZ9DkauKS0kuYkTqDrW1beWH3C6xtXktFWgVXTbuKOelz2NWxi39W/pP3696nyF7E5aWX83bN21xWfhnrW9bz4p4XyTHncNPsm5ifMR/poB14V8DFyvqVPLb1MTQqDTdW3MiS7CXRHfIxYNTmzE/2tfPgB1VUtbk4a3oGly3MZV+rm0c/3E+PN8hlC/I4pSyVHU29/OX9SvQaFV87rYRlJakYdRPwvJRlJdxv5Z3QtR/mX6dIPbdshy0vABKUnQPZ82HP67Dhb2CwK/cLjkLY8pyijpVaAifext7kXJ7a8RSrm1azNGcpV027iuLeTvjgTmjfDbOvoGPOlazp3M4TO57AG/RySeklnJh1IiXJsfK7Ta4m/l31b17Z+wqF9kJurLgRjaSJnrOzUmdxxbQrMKqNPLL1EXZ27uTconO5sORC9nbt5a9b/0p3oJvPTf0cZxacGZe7NA4ccwW1jwWO2gmJHiBJNpR0jwSVcuL6pgFBWZa7JUkyAm8Cd8iy/J8Bfc4DbkNRx1oM3CfL8mF15kb6Zq/HEyAYjrCnuZfqTg82g5bp2TampFkOe1yHy08oEiHDZqTHG0CjUmHWa+jyBDBq1Ri0R7Ek7HeBHFYmFlDyRFq2g6dL2YbtbYTa1coq9pTlkFQIgM/vxBdw4fD04GnZSigcxObIp5cIKpUGs7cHqj+kM38hG/Q6VrdtptQ+hRMMGeTteB3yF9NTsJRuOUBBGKhfraz0pU2j15GHSq3BbEqlx9+DTqXDqDUmNj/kxxvyYtfb8Ya8BMIBGlwNvF/3PgDLcpcxM3Vm3MpIKBLCFXBh1pmJRCLRMQ6+oE4AJr8TIstwVwmc9Vuwxu/iHeBbK7/NxSUXDTkx/aXdZnZ26rig2H3kzoChux5r83ZqT7o12hYhwj3r7+WeU++J260bCp5AiNue28i6H54+OW+OD82oOSEH6PYE0GvUGPu2tjpcPlqcfpqdXiQkMqwGpufY6fUGkSQmpjKWv1fJtdv7Fjhyofg0SD+MUpS3B9p3wf6PIamgv7hnyZlgTlWEQ0I+SC5SdkSat0BXHb6ZF+JLLsSgt+EL+XBojBBwE9CZ8YS86FQ6evw9pBhT0Gn6V779IT9N7ibaPG28WfMm01OmsyhrEVmmLFrcLVh1VkJyCKPWGN0B7/Z1Y9Aou+5b2rbwYcOHOPQOTso5KWYBoTfQiwrVEes/jAKjOmf2eoM4fSGy7HpUKhU7G520OH2EIxGSLXqmZ9nQa9U4vUHUKjDrJ+B5eTABr6KSaUqGYBBqPoDK95Twv+LTIGse9NQoYdxqLVgywZYNjRugq0aR6s2qgJSpBCNB3AE3Fp0Fjapvzgt6lYdJmds3Nm9Eo9aADMFwkPLU8kM6qQfOtwPnnCfooc3TRoohBUtf2NjA+4AD1/BuXzf+sJ8Mc/wO6jgx4W4uBINTx1qAkpxu7XveA9wgy/L6wxyWBfxNkiQ1SujXi7Is/0eSpJsAZFl+EHgNxQHZhyLRe/1QPshwsJt0/PWjKn7xn/4kv8IUE09/aTG5SYdePUqx9Ie22I39F5Yk0yBqHOgPcnR2vAr/ukXZak2fBpsGJCPmLobPPw2WdAx6G4bOanj8HEyBvthNScJ69h3Kqt57vyKYMYOnzVoeqXolOsR0ewl/0hWQ9tIXsc+5CvuSr8JjZypxz31Yr3wBSpVwsSPJ5eo1evR9IT4mrYk9XXtilFke3foofz37r8xNnxtznEalwdFXXRgV0TEEo0DrDmXL/zAOiDfswxXoxTEM9ZJa59HngwCEjHa0B4VjqVCRYkyhxd1Mob3oEEcePSadhtJ0Cx/ta08YRik4NI6D5rEdjb184fE10fxYk07N3286cWLLn+76L7wyoNCb5V647nVInZq4f/tueOI8WPETZR4+ELO/5iHFiX/j//oThM/8DbzzMwgHMKz+M4aLHoWKS6M3a2j06ADdgflRl/ha8szOZ3h+9/PR5wszFnL3KXeTZU0cQnRg3lxZt5Lb3r0t2v7Y1sd44pwnoiFaAxOGjyWsRi3WPjGEXU1OLnvoU3r9/bkhj127gNOmZWAzTgLn4wA6o/IAxQF5/sr+c2/to3D5M/DCNSD3fc6MWcqOybu/7B8jtRSueQWtPbf/2noArVF5AOua13HrO7fiCSm5chISd59yN2cUJCjMCXFjmbSmuGKaA+8DDnWcQJCIweSE/BW4RZblQlmWC4FbUZySQyLL8hZZlufKslwhy/JMWZZ/0df+YJ8DckBB61ZZlotlWZ4ly/KYLyU3dHm4+809MW3VHZ5DK1uNFr0tykUNYOrpfduxA6hfDW0D1KSq3lNCuQ4gy0oC8oa/Kd1nXMDj1f+OGWJHz172Jfdti256Rqkd4T/oc773u1jlrkHwz33/jFFmCckhXt7z8pDGEowQle8qISaH4UBSumoYi0W1vRrSBuOE6CyoAx5FC38AyYZkmjwjkxcCUJHr4K0dE1QdZ5LgC4Z54L19MQI9nkCYD/ZMnITnOFyt8M7P49uaNh/6mM3P9dcJGZg0LEdg35ux6nJbX1QKFB7gnZ+De3DfR21vLS/sjp3n17aspbK78hBHKLgDbh7Y9EBMW2+wlw0tY1Jia8Kwan9HjAMCcO87e3H5J4+4SRy7X48/99Y9Duff2982dQV8eHfsce17lCiKI/Bp06dRBwQU0YMntz9J7xCv+QLBcBiME9Iry/KHB57IsvwRcEyctaGITCAcr/oQTNA2qkRCypYp9KljJbihG3jDFkgQ9iJJEFQmmLBKHeMQHCA48D4zkWJF0JX4vY+CRIoazsAYO3OCWPa9e1hVLOhLSh+GMpYyxlHK8x5AkggabOgOUopL0jtGLDkdYF5+Eu/vbiUSGVzoqaCfiCzH3eyBEu42YYmE++fTgSRQn4ricyriDcEEimpBb3Q1WXnuiX+eYL49HKFICDmBqtGRFAJDcijmRvIAvkRqS8cw3kD8NdrtDxGezL/1RNf1gAsMA6ImVNrE5/FRKFAlUq/yhrwE5UnsuAkmLYNxQtZIkvSQJEmnSJK0XJKkPwPvS5I0T5KkeaNl4FiQ7TByzQmx24tWvYayQ6hjjRq2bDjxq8q/G9bDlFNiX7dmx1a7Ll4RX3hOb4EKJdE3p/IjzspeFvNyiiGFYnef75i7GJKnKoUSB7LkG0qM6RC4cOqFcW2Xll46pLEEI0A4qOygHcEJqXXWkWpMLCTw/+yddXhcx9WH31nQ7oqZ2ZKMMnNMceI4zIwON9SmSZsG2jRNmybtlyZtoGHmOpyYkxhiiplJsiVZZDHjwnx/XHml1a5t2WJ73ufR472zM3PnStdz75k553c6Qk2zoMku8PM6PsPdbg7Aq93qcbA5mILarss3ERlgxmLUs6PAs2S14th4exm4faprXlqdgOlpfVgRzj8KJv/atcxg1lxZjsTIa7Vs1dGj3L9LmQUH2+iwDL1Y22U8zORfH9Xl0RNxfnFMjnZVQYzxjSE54Gg5gDU32TlD57iU6YWeMRFjjuv8/Z0JycHoda67t3dOS3Zxj+53eBIPGXU9LPhD6/GBpTDyOtc65kAIG3LM7idFTXKL0bxy4JWdSlKrUJwoxxOpObLl3z+3K5+MJql7zJwhfRWjXsdtU5OJDrQwd0Meg6L8uHVKEinhPWyECKGpsViCIXu5ppYVN0HbYg2M1+R7A9soR8WMgRu+hlX/1tywxs4Ba6Mm9Tv7aSwHV/NAxFQGhQ5je+VeoizhXB4+npjM5TDzjzDkEi3Q/YZvtD7qSmHCryBt9glfwpiIMbw480Xe2f4OEsnNw25mbOSRE+Qpupn8TZpxa/Y/arW82lxGho084dPk1RiI8LZzvLoCVrM/XrWuuQKCLSFs7GK3kpFxgfywq4jhfTFrcj/h9EFh/Oeqkby58gABFi/umjGg7/8+R16niX5seBuCkmDyfRB1FCMk4TS48VstFu/cf8GOL7QV53G3QlAyJE6D+lIYdpkWuD7wXG2VeujlMGDGcQ/P18uXxyY8xuKcxZQ1lGExWDgn6ZwOBfOeGX8mRp2RD3d/SKg5lFvSb2FIyLFfQk8mhscE8OGtE3h1eSZldc3ccloSMwcdM3NA3yZqNFz+Duz+VnPFSjkTYsbBrCdgzwItg/ro67V3gpA0bZHJJ1x7PwgdcMzux0aO5fkZzzP/wHwc0sHE6IlMi53W/delUHigw0aIlPL07hxIbxMdaOG2qclcMz4ek0GHQX88m0RdR7WXNxujUljSfIB4Wc4ZCeNJLTtAbtJprCxex+Y97zA5ejKToiZpD6rk6RA/SdvCzd8AOz6nNmwIG6NSWWzLY7y3N8HShKk6mzCfSLL1gpeNdYwOSWNSXQEpy5+BQefDxa+Bl7f2A1pMSM4a2PW19hI7+EJNfeMYmA1mZsTNYGLURBrtjews3clTa58i1DuUWQmz3B6S2VXZLM9bzq6yXUyPnc6EyAlHlPZVnADZP0NE+9Q8rkgk+bX5nJVw1lHrHY28GgNhx+OK1YLNHIBXrWsej2BTECUNJTikHV0nsre3ZWR8EJ9vzOWBs05MflihiW9cNCqGs4ZFohfgZeiav0234hehGRDDrwK9CQztgpWtTZC3TpPeDU3R5FINZk0qNXIEDL8SkJohU7AFBp0LzfUQPhQcVghOJiNhHD+VbCJr3WrGRo6jrLGc5IBkIn0i+Tn/Z/ZV7GNS1CQmRk10C+gFzfXKYrBQWFfIkJAhHl1oQVO72nBoA0tylhDnF8cZ8WdwUcpFnJVwFnqdHq92+SZsDhvbS7ezMGshEsnZiWeTHpaOUdePAraPgUGvY9KAEMYkBGJzSLz7ogzvsSjaCXvmQ1kmDLkQ4iaByV9TY7M1gU8YWIK0WCWzn3Zs8qNcJ1gfGsVPzeEMDEhihl5w9P0zDYvBQrh3OFE+UVQ3VxPvF4+3wZt1hetYkLUAXy9fZiXMItwSztpDa1mRt4J4v3hmxM0g0ieS1QWrWVu4ltHho5kSMwWbw8ayvGXsKtvF6bGnMy5qnFvSW6vDyrbibSzMXohBZ2B24mzSQ9NdJP8VpybHkyckAvg7EC2lPEcIMQSYJKV8qzsH6Ik+K4XaBfxv7//469pWxYsgUxBvpN/Dk/vnsq1ir7P8ogEX8djEx1plTPd8D59dD+ZAvpr5Wx7f9SaDgweTGpTKt/u/dbZL9E9kQtQEPtv7GTNiZ/AEIYT8/Dyc+YSmPX54KXvbXPjyttaBmfzhlkUQ0fGVtsXZi3lw+YPOY2+DN++f875TRvJQ3SHuWHwHWdVZzjq3DLuFe0fd25celP1bovfd8yFpBsRPOGKVyqZK/rjqj9wz8t4TDkt/a5sfVU06zkjw4IN/FDSZ3u0cnHKfS/mr217j0QmPEGbpmlVNm8PB3R9t4ocHphPhbz52g75Pt0v0nhLsXwofXgKz/gpL/tSqfKXTw5z5EN+SX6ZwK7x9dmusyPQ/wLrXyb74BW7a8i/KG8udXd467FYc0sGy3GUuc9sVaVfw+7G/d5E7r26q5m9r/8aC7NbkdIODB/Pc9OeI9XdN/Pj5vs/5y5rWQPtAUyDvn/0+SYGeVeQ2F23m5kU3Y5fa4oBO6HjrrLd6Yme6f8+ZPUlpBrw9W5PePcyVH8AXt7TGfwoBl78Ln9+s7YwAjoh0Xht/Of/d0fr6FeMdxVunv0hM6NEXWnaW7uSmhTfR1BJTYhAG/jHtHy7PaqPOyDNTn3EpO7xItThnsbPsgTEP8MW+L8ipyXGW3TbsNu4ZdU+rPDCwrnAdty2+zRn/ZBAG3jn7HUaGj+zAL6nLUBK9fZDjWe5/F1gEHE57uQ+4v4vHc0pTUl/CS5tfcimraKpgl7C5GCAA3+z/hoPVB7UDWxOsfxukpGzoRbzcoog1NXYq8w7Mc2mXXZ3t9P1clreMzPgWH+Ll/4TKXO1zfTksfcp1cE3V2k5LB6luquaVra+4lNXb6tlcvNl5nFmZ6fKQBnh/1/vk1+R3+DyKo2C3ajryEUOPWi23Jo9wS3inZujcauNxyfMexmoJxKuuzK081BJCYe0R85UeNwadjhGxgfy4+9TMnq7wgM0Kq1+EqJHajmHbBTmHHbb9r/U4e2WrASIEIKGhgr22GhcDBGDuvrnE+sW6zW1fZnxJZmWmS1lGRYaLAQKwu3w3eytd5/vShlK3Z0NlUyW7y3dzJL7Z/43TAAFwSAef7/v8iPUVvUDhNlcDJDAeMha5CtBICRvfhbjW9Gn5g2fz1u4PXbrKry8ko2IPx2JNwRqnAQIwOmI0n+z5xKWO1WFlbeFawiytMV/JgckuBghoz/S2BgjAu7vedXmGSyn5dM+nLgIMNmnj+wPfo1AcjxESKqX8H+AAkFLagBOTUFJ4xCEdHrfiHdJzsK+zXOKctBx6o7MPHTqPbdtOBq192Gn502qrLZ5cAo5DMUsiPSq8tL0+u4f+HNJxxOtVHCeFWzUxg/a5aNqRV5Prtn1+vOTV6o9PGasFu5cPOlsjop2qT7ApmIIuNEIARsQFsmR316luKfo7Uov30BnA7mG+s7VRH2r/fYvBYvcwVx1J8crT3HbEud3hXs8m3cfY1shoT6PdXSmr6WjKYIqep/3fX2dwkywHNNe/NjsLDqH3+Pz0dD+2p/1z2aAzeHxW2x12twD2jiClxIHrOJoc7vddcweUvBQnP8dzh9UJIULQXnkRQkwElNxMFxLhE8Ftw29zKfM2eDNI50OyX7xL+fTY6cT7t5QZTZoPMxC281tuSzgHgHWH1nFG/Bmu5/COoL5lRW9M+BgGlBzQvphwNwS0BL37hMLUB13aYTBDTMdF0AJMAdyW7notRp3RJWlhSlAK4e3cbS5NuZRYP1c3BMUJkr3q6NmhWzhYc5BQy4mrHNkdUFR3fIkKnQiB1RLkITg9mPzavBMekydGxgayLqucRqtaO1EABi+YdK9nJUKAEVe1fk6aomWqBs0AMZjA6M1Ar2B8jK4ZyS9OuZjyhnIivF2Dy2cnzmZAgGvg8ICgAZwWfZpLWbxfPClBrskUw73DuT39dpcyi8HikiG9PZ6UCq8ceOUR6yt6gchh4NVmkaj8AKSehZvCx6jrXZTZovcu5urUy1yqBJmCnIkqj8ZpMaehbxNrt+HQBrf7Qid0jI8aT1F9a36l3OpcJkS6uvVa9BZCza4LWJemXkqsb+szXAjBtYOudRvHBQMuOOZYFSc/xxMTMhp4ERgG7ADCgMullNu6b3ieOZn9SMsayvg572e+yPiCZP8Erog8jWFrXufA2Bv5sfEQeQ2HSA1MZUbcDNeX9YYqyPwBNr1HRcJkVkYkMjdrPucPOJ9aay0/5PzA8NDhjAgfwSd7PmFM+BjOCh3B4CV/0xRk0s7WJC0PU1+uyU+uf0tT5Bp3O8SNO65rqWqqYk3BGj7d+ykRlgiuHnw1I8NGItpMsPsq9vFVxldsK9nGucnnMjNuJlG+njMF9xL917/5w8u05GqJU45a7Y8r/8gZCWcS5XNiGcULavX8flkoD42vOKH2IRk/Uh03lurYVnnR3No8Vuev4vFJ7cX4OsdT83bxwFlpzBx0bPWhPo6KCekKmus1Bbkdn2sJPXd/C3ovmHiXFiBsbMkC7XBoAey/vKYlPEy/QtthzNvAzkGzmHtwMfvr8jkz/kz0OgO+Rl8S/BNYnrecisYKEvwTmBo7ldSgVLch7Cnfww85P7C6YDXDQ4dzbvK5DA9zFwEpbyhnZf5K5u6bS6J/IlcNuophoUcWnWiyNbGpeBMf7voQh3Rw/ZDrGRMxpjWje/fRf+fM3qBgM+z8BhrKNZGZxCnaLvam97TduFHXQ+x4KNwC694A33CYcCdFvqEsy13Gt3lLGRaQzKUDLmJg1LHjfewOO1tKtvDR7o+obqrmmsHXMCJ0BNtLt7OyYCVeOi/OiD+DcEs4y/OWsyhnEfF+8VyaeikRPhEszFrI0tylTI6ezPnJ59PsaHY+w89PPp/T408nst2zpNHWyPpD6/lo90cYdUauG3Ido8NHu4kpdDMqJqQPcjxSEgOAc4A44DJgwnG2P3UpzYBd30DOKhh8gbbSEeB5tT9ECi62Cs73SkFPIMIvHq76iPryvTQV5FFQU0CCXxwNDWXgE62t4m3+QJvARt0IV7xHkJcvFxiMnJN2OZVNlawpWMPYiLGEWcIINYdyYdKF+Hj54B+cCjcvaF3ha4t3MKRfDkMuAqEH3fFvywaYAjg76WzOTDgTndB53NpNC0rjD+P/gNVuxehpHIoTw+GA3PXaPXEUbA4bxQ3FnXLHyq0+ziSF7cdgDsCrxjVWI9Qc0pKwUNKVz44RcYEs3ll0Mhghis5QVwZZy2HbZ5ry1cjrNPENaxOEJMKmD2HTB5pketxEbdckfqL2MigdWn4m6YBhlzHUYWNIwunkVOcwL2s+20u3c8GAC9AhQUoK6gpICRxAs62Bt3e8zS8FvzAjbgbT4qYR4xvDoOBBDAoexK3DbnUJWm9PsCWYC1Mu5Nykc9Hr9C6LOZ4wGUxMip7E+MjxSKRLoLCiB6gqgMwlmsJk3EQtr0yYh50rodfcn2sKtR02gwW8QzQJfodNk981+2vKlXETwegNOgMRQQO4KjiFS4dch0FvQuh02k7KnvmQsQQGzoa0cyE40fV0QqAXegYFDaLJ3oRJZ8LmsNHsaKakvgRvgzf1tnrCLeHcMPQGrky7EqPeiK7lHeD24bczZ+gcl+f1sZ7hZoOZqbFTmRQ9CYFQqlgKJ8czK/1JSjlXCBEEnAn8C3gFzRhRHInqQk21qqQlYGz/TzDiGjj/eddsu4fZ9iksfKT1D7PyOQ7eMo8//fKkM6hx7aG1bI6dwV+G3Unwu+e2Zknd/R1c+SEM0bY5HTh4Zesr/G9fa4BljG8MM+Jm8NHuj5geO51npj6D79Fe/rvAMOjIw08ZIF1MyW4w+WnG5FEoqCsk0BSIsRMvKHk1BkJOxBWrBaslAHO1a/yHxWDBS+9FeUM5wZ1Iotie0fFB/GPhHqSUx3yJU5zEZC6Br+5sPd75JZz+R00V65OrW4PUd36h5VFKnq4d63S0ejG3/Ks3crA6h5sWzXEGqScGJPLS5pfIa3EpXFu4lvOTzienJoftpdtZXbiaXwp/4ampTznduY5mgLTFoD++/6vqha8XsDXBiv+DjW9rx/t/gq2fwJzvXRcgS/bCexdAY6V2nLEYrnhPU8dyxnz8H1z+Nnx5e2vZzyZNrTJ6FMbD9019OXx9DxxcrR1nLYN9Lf1ZApyn3Fm2k5sX3eyMzzToDPx18l95ZOUjzjqLshfxwhkvMDVmKqbDu4Ft8PS87sgzXBnCivYcz/L24f8R5wGvSim/AfpxWtIeomRPqwFymG2faisW7aku0FSq2tJYyb7ag26qKsvylrG/saTVADnMyn9pOUOA3JpcPs9wVUPJr83Hz0tLwrg8bznZ1dnHfUmKfsDBNRBx7HiQvJpcwrw7l/U6p9pAWCeMEJsl2C1XCECoJdT5EtdVRAdaMOp17Cyo7tJ+Ff2I+grNraotdqsW/Ju73lUlS0ot0eEx2Fe+z0Uly8/Lz+3enZ893yU7+o+5P5JT7aospDhJqMiGTe+2K8uC4nZqZoe2txogoCUP3rfQXQRm43ta4uLD2Jog62fXOqUZrQbIYQ4shbIMl6LV+atdBGLGRYzjs72fudSxSRur8lZ5vDSFois5HiMkXwjxGnAlMF8IYTrO9gqFoqfIXgVhHQtKD+tEUDrAwWrjCSUqPIzVEoCxvsLtwRtiDiGvtuvlmkfFB7Jop1LJUigUCoWiNzkeI+JKtDwhZ0spK4Fg4PfdMaiTirBB0D550PCrIdhDblP/aJj+kGuZOZA033hSA13VUmbEziDFEubuLjXlQfDStvfj/OK4PPVyl69jfGOoaa4BNIWtRP/E474kRT/g4NoOKWPlVB0kzLtzCQHzaw2Ee3vO8twRpM6AzeSHV12pS3moJZTcmoOdGpsnRscHsWRX0bErKk5OvINgwp2uZXqjFpAeN85dmWjsLcfsMi04zZl/CbTs5m0VggDOTTyX1QWtK9Uz42aS4O+eQV1xEhCUCKPntCtLcp+TI9PBHNh6XJGticS0d6EbcxPk/tJ6bDBB0lTXOqGpED/ZtSz5dAhxFUOYHDPZxS1qfdF6rhp4lUsdgzBwWqyraptC0R102EFPSlkPfNnmuBDoWiH/kxH/KLj6I9j1LeSshMEXQuosz/EgdhsMuwJ8IzX/0dBBMPwK4kPSeHLCn1hasJJtJduZGDWeaZHjCQodAnMWwJYPtYRHo+dgi5+IcNjR6/R46b24Y/gdDAkZwuLsxQwPG86g4EF8vu9zHhn/CNPjpuPbVh6wF1GB6V1IVZ6WWM3fs/jBYSSSvNpcZsbPPPFTNemwOcDX2DGVvSNh9Q7Gq+YQzX6tAeNh3mFsLel68b20CD8KKhvIr2wgJrBjfviKfoq9Jb9Ce8MiZRZc8S5s/RQswTDuVhAGLUHhRf/VfPglMOZGLRjYYddcs44Qj5Hgn8Abs95gQfYCdpfvJj00nXMSzuKHgz+xp3wvU2NOY0zEaNYVbcTP6OcMTG8r79tTc6DdYVeB6t2NwQTTfq+5UJXs0ubi5OnugjRhA+Gm76BgO0gr+IZpbW6apwnOWBtg9I2acts1n2I7uA6d0YIuebqWZLMt3sFw8ctaYPr+HzUBnLRzXOJBAIaGDOWd2e/wdebXVDVVcWnqpaQGpvLs9Gf5fv/3+Bh9ODf5XMaFHZ8aZnsO58VR95niaKi7oycITYVpDwIPev6+qQayVmh+yiY/mHQ3XP0J1BZpAZPzHmDYhLsY1qgHyyBo1IEhQAuSjBsHceNosDWwrnAdHy7/LRaDhesGaxJ4ET4RXJZ2GZeltWqKn5Fwhudx9AIuEr1J5zIzvs9J9PY/Dq6FiCHuL17tqGjxRe6MIZpbbSDSx36sUx0TqyUQU80hahnhLAu1hFLSUILdYUPfhQ8yvU4wOiGIH3YVcdPkxC7rV9GHqCnSMk9veh/Ch2i7GdEjW7/3CYGhl2jGSPZK+OlvmurQxLs0FayRLXkN7DZtBfqXVzXf/fF3ai+TJj+3U6YFp5EW7JqnYUSEa26loWHDuXnYzS5leTV5LMlZwpKcJYyPHM+FAy4kOdDDTnknsTlsbCnWpFlrmmu4dvC1jI8c32cWok46pE1Trcxeqe1QHCnZb2MVZP8ElQdh6GWaG23CJO2nhermatYa4VPrAUIMIVxr1DMCia69cmBwMky+V/s5AjqhY2T4SEaGj3Qpj/SNZHbi7BO9WidSSraWbOWT3Z9Q1FDEVQOvYnL0ZAJMAcdurDjlUEZIX+DAcvjsutbjvfNhzjxNE3znlzD2Vlj2FJTtb62TdjZc+iaYtYfh+sL13PtT68SzLHcZ75z9DmMiWnMv9DXya/O5a8ldFDdoQcnbSreRWZnJIxMe6Wn98JOLnNXaLtoxyK3JJdw7olMCuAdrDIR1whXrMFbvIMxVBS5lRp2RQFMgBXUFxLVL1tlZRscHsWBHoTJCTkakhI3vwrK/a8d562HnV3DbD+4Sqdk/a2pYh9k3X9tdPvwCWLAJ3r+g9QUyawVc+QEMubBLhlpnreOf6//J0tylAGwv3c5PB3/izdlvEt5JN8n27CjdwW2Lb3NmWf/l0C88P+N5zkw4s0vPowCsjbD0adj6sXacv1F7lt+ySMu7dZjcddr911zbelxfBjMfc+luRd4KHvm5Vb3qh4M/8P4575Memt7dV3Lc7CrbxS2LbnFmYd9YtJEnJz/JJanuyTMVChVY3ttYG2H1i65l0gF75mnJsUDLYN7WAAFNQaNCU9iyOWx8sPsD1y6QLMpa1F2j7hIyKzKdBshhvsz8kryarlVEOuU4uKZj8SDV2Z0OSs+pMhBqcXSqDwBbiztWe8K9w8itye10/+0ZHhvAtrwqquqtXd63opepyodV/3Yta6qGQztcy2zNsOYl1zIpNanzw+xb7L6Cveo/mrtjF5Bbnes0QA6TVZ3FgUoP6omd5Of8n50GyGHe3fEujbbGLj/XKU9FNmz7xLWsOt+zOtZhA+Qwv7yqSfe2UNNcw5vb33SpYnPYWF+4vgsH3HVsKdniNEAO8+b2N6lqrOqlESn6MsoI6W2ETvMfbY/BpCWcgyO71YjW4DWT3r2Pvr6b4Em//khJDRUdpLFKk4IMSTlm1ayqbCJ8OrfamlPduaD0wzRbAjE2Vmo+/G0I8w4ju6rrZUxNBj3DYgL4YbcKUD/p0AnP+Y3c5hsBnrKHG7w8f3aWmeiqBJpHylXTHbk9DMLd8cGgN6h8Od2B0Gk/7Wn/d/VUR29wKdcJHV469/uwr8ZaeBqXUWdE6NR9pnBHve31NgYvOO03rmV6Ly2gbOA52nHlQS0wrS0jrnUqbBl0Bq4fcj2izYPRoDMwK3FWd46806QGppLkn+RSduOQG4nxi+mlEZ0E5K3X1FA6EOB6sCaHcO/OZQ7PrTYS0Ql5XidCj9UShKnW1SgI947otlw2Y+KDmL9daWucdPjHwIxHXct8wzUlorYYjDCpne+83giDzm89Tpnlvkg05beehUVOgAT/BC5OudilbHjocAYEDOiS/tsyNXaq28vsrcNu9biApegkQUkw/leuZWGD3Xeoo0Zo2dHbctr9WhxpCz5GH341wrUvi8HCuKjOBY53F6PCRuFt8HYpu2vkXfh7+ffSiBR9mb5pSvdDGm2N2opF290HKbWtVqO3h1W4NiRM0RQytn+hBTwOvVjz6Z/6ICTPoK4iG3P6leiLd2u+pQNmwoAZ4NX6H310+Gjenv02C7MWYjKYOCvhLBd/0br6MkxGXwwesp96uhYAs6dVwi4kwieCF2a+wPK85ewq28X02OlMiJyAUadUsk6YnI65YtU211JnrSfIHHTCp6qzCmqsOgLNnXfHAmj2DsFclU9TGwWZSO8I8mpykTgQXbxmMjohiPfXZFPbZMPXpKbCfoNzXvVpyWDugeFXQUAM7P5ee6EbdB6EeHixjxmtzb07vtTm0yGXQEybOLrokXDzAtj5NTRW0zzmRuyhqRzRBLHbwNZIk95InbWOYEvwkWoC2hx778h7GRsxllUFqxgVPoopMVMItgRTZ63DpDd12Yr30JChvHv2uyzOWUxtcy1nJ53NyLCRXdK3oh0Go7a4GD1Kc52OGaOpVflHa26ATVVgCdHuv6s/hr0LNBeugedA4jStD2sjIMFoYXL0ZF6b9RqLshYRbAnmzPgzGRzcMs831YDBckTlNtDct5rsTS5qbM32ZhzS4fKc9/Qec7z3YVpwGu+e/S4/HPyB4rpiZifNZnT46GM3VJySdOuTVwgRB7wPRAIO4HUp5X/a1ZkBfANktRR9KaV8sjvH1ZVUNVWxMn8l7+98nwBTALek38KYiDEYK3K1oLTd30HiFC24PGKI505sTVBXCg0V0FyjTUY//4vcwWfzrb2SJaVLGa2r5OqBV5M26W6PXXjpvRgbOZaxkWNdyvNKdzMvaz4LCn5mREAq1w68ioFRYz32UW+tZ03hGt7Z8Q4GYeDmYTczIWpCtxojiQGJJAYkdlv/pxzZKzXRgmNVq8kh0ifSXV3lOMitNhDhbaOrdtmt3sGYqlyTE1oMFixGC4fqDhHlE901J2rB12RgUJQ/P+0p5sIRXdu3opsozdSkS/cthOQZMOZmCPcgwuAdBIMv0H480VAJGUsge4W24NNQob3MNVVrL4mHF2uEgJgx2KJGsLl4M29tf4OKxgquG3Id02KnEWgKbO0zfxNs/oAN6Rfyadb37K86wMy4mZyddDapQameRgFoizEXpVzERSkXad3U5vPmtjeZlzWPoSFDuW7wdQwOOfbCwrEQQpAelk56WN8LZj4p8YuA4VdoP4fJXadlP8/foN2/I67R1NjiJ7bWsTZCxg+w8jmwNcLkX2NOOYPJ0ZOZHN0mD0hlLuz4ArZ9CpHDYeLdrgpwLewo3cH7O98nozKDi1MuZnbCbLJrsnl7+9tUNVVx49AbGRsxlk3Fm3h/1/t4G7y5Nf1WkvyT+PHgj3yZ8SXJgcncNOSmDt87g0MGd8k9qzj56e7lPxvwoJRykxDCD9gohFgipdzVrt7PUsrzPbTv8/yc/7OLasUvh37h3bPeYtSiv0LWMq2wZI/2wLtlobYS0p79P8LnbWQbd35J/aVv8s/8BSwr0oLT91fuZ0XeCj4454MOS9g2NFTy763/ZVHeMmcfy4vW89EZrxLjQT1p/aH13L/0fufxxp828vqs15kUPcmtrqIPYmuGQ1s1d5FjkFOVTUQn1Xdyqg1E+HSBK1YLVp8Q/Aq3u5VH+kSRXZXd5UYIwNiEIL7dUqCMkP5AfQV8fTfktSRtK9kDmT/BnO+1F77jIWMxfHsvTHsIFrdx3drxuaZMmDjFpfrO0p3cvvh2Z2D3Yysfc1X8KdkL71/Izste4Ter/0h1czUAmZWZ5Nfm86dJf3JZhT4STbYmXtnyCt/s/8bZfnnecj469yPi/btWIU7Rw5Tsgy9u1dyrQbt/D22Hy99xvX/z1sNHrZL6zL0JrvrQ1aC2NcPPz8HGt7Xj4t2wbxHc9hOEtu74Hag8wG2Lb6POWgfAsxueJdgczGMrH0Oi5XZ6YvUTPDz+YZ5Y84Sz3fpD63l6ytP8Y/0/AMiozGBF3go+Pu9jUgKPHW+oUHSUbo0JkVIWSik3tXyuAXYDJ43Df521jvd2vOdS5pAOVuevgpJ2KhiVOVC6z70TayOsfdm1TEpyhc1pgBymqL6IA1UdV03JrzrgNEAOU9ZYxv6KDLe6Uko+2/uZW/m3+7/t8PkUvUzhFgiIA69jv+zsrzpAhE/n4kGyqoyEWbrOCGn2CcNUXYi2adpKpHcEmZX7PTfqJOMSg1mzv5SaRqWS1ecpP9BqgBymbB+Uuc9nR6WpFla/pOVuyFjs/n1bdawW1hetd1OWemfnO9Q012gHxbugqYZMe53TADnMguwFZFVl0REK6gr47oDr+SubKtnfTfe/ogcp2d1qgBwmZ5WLEhaguf6155dXXUU7qg7CZtd3DxortcSIbciszHQaIAAh5hA2FW1yGiAAYyPH8kXGFy7tJJI1hWuI8mld8GywNZBRfpz/1xSKY9BjgelCiERgFPCLh68nCSG2CiEWCCGGHqH9HUKIDUKIDSUlJd051A6jF3p8PLzweRssYG/20MCTYosOTO4BWwahRy/c40iOxz9YL/SelSo8+I4KITwGjvl5uSflUrTSp+7L7FVaYrYOkFOdTZR355JCZlUaifTpvDLWYRwGEw6jGWNtmUt5tG80mZWZXXaetviYDAyJ9mfxzpNPJatP3ZtdwZF83o83y7jQa7F3tgYtXq89HhIRmvXuLqm+Bt/WOboljs3gQe3IS+flUZnKEzqh81i3JzKp9xQn3X3ZUTzFOgoPSm5mD89cUwAuimzCAJ4EBdopYrZ//lsdVrd7udHWiMXgHuVkMVpobvceYzhK3IlCcSL0iBEihPAFvgDul1JWt/t6E5AgpRwBvAh87akPKeXrUsqxUsqxYWGdy23QVZgNZm5Pv91Flcrb4M3EmNNg2GWulROneU4gp29Rx2ork2j0Jr65iesSz3GpOjJs5HFthcYGp3Fz6lUuZUMC00gJ9uyreeXAK10MH6POyHnJ53X4fKcifeq+zFrRISOkqrmKBlsjgZ0ISgfNHSuyC92xAJp9QjFXueaJifSO5FDdIZrs3ZPPYGJyCF9sOvly0/Spe7MrCEmBkde5lqWeDaFpnusfCS+LJvqRtx5SZ7nKpBrMMNB9zhsfOR5fo2tm8TtH3on3YSMmajgEJTHILkn0T3Spd8OQG0gJ6ti8Hesby+3Db3cpSwtMIzXwyDEl/Y2T7r7sKBHDIG6ia9nwayCi3brr4AtdpaOFDibd7WqEByXA9D+4tgtNc+trYPBA4tskeq1urmZs1FgX9arNxZu5bvB1Lu8xFoOFyVGTKWtsXRCK9o1uDYZXKLoIIaU8dq3OnEAII/A9sEhK+VwH6mcDY6WUpUeqM3bsWLlhw4auG2QnsNqtbC3Zyoq85fgZ/ZgSO1ULyKo5pGWuzlmtBYslTYPAI/j02po11at9C7SVubgJkL2S0ujhbPLSs75kK4NCBjEhcgKxfrGe+zgC5VU5bCrayC9FGxkYOIAJkROIC/O42YTdYWdH2Q5W5K1AL/RMjZnKsNBhp7qOfIcvvlfvS7sN/pEAl7wG5oCjVt1cvJl5B+ZxedrlJ3y6qiYdc+aH8+fJ5UdMY3Mi+OdvxqH3omTYRS7lH+/5mGsGXcOgbngINtns3PvxZn56cDrh/t2rCNeFHNdvvS/NmZ2iulBzYTm4VlMWSpzamoFaSqgvB5Ov59xLoMWVGEzQXA9VuXBgBQTFQcFmbQckdZamaOSBveV7WZW/ioqmCqbHTic9NB1T2/OUZsCBFeyKSGFtdQbZ1QcZFzmOMRFjiPbteMxRRWMFm4s3s7ZwLSmBKUyMmtjf4kH6x5zZE9htUFMAlmDtvjy0Ew6u0mJBYsdB/CQXOV5Au48Lt2hxpLZGSJ2tqWu134Wor9D+HxxYCmFpWqC7h/xQWVVZrC1YS3Z1NpOjJzMqfBT5tfmszF9JTXMN02KnMTR4KLsrdrM8bzk+Rh9Oiz6NBP8ENhdvZlXBKuL84pgcNZmkwCS3/vsRp/SLTF+lW40Qob29vgeUSynvP0KdSKBISimFEOOBz9F2Ro44sD41cdWVwZ7vYfv/tO3RCb+CpOmt6iodoTIP9s6DXd9qUr6jb4SUM8ES2G3DVnSY/vFAzd8In98GF75wzKqfZ3xBZWMFU2KmHLPukdhc5MWb2/y5Y0T7jc3OYa7Mw+/Qdg5Ouc+lfHneciK9I7kw5aIjtOwcb/y8nwlJIdw5vevzM3QTp6YRciTKs2HTe5paUGS6ttMR00YWtOYQ7PwK1r2u5QxJvwIOLNfUtZKmHr9Ll+Jo9I85s7sp3AqbPoCMRdoO9eRfgyUI1vwXyvdD1EgYd4u7EaLoLpQR0gfpbge/04AbgO1CiC0tZY8C8QBSyleBy4G7hBA2oAG4+mgGSJ9j7wL47tetx/t/hDnzIfG0jveRsQgWPNR6nLUcrv4EBp3bdeNUnNxk/QyRwzpUNbMig/Sw4Z07XZWxS5WxDtPsG4apqgCkw8VNJsYvlu0l27mQ7jFCpqSE8cHaHO6Ylnyq7/z1P6wN8ONfYOeX2nFlDmT/3KIU1LIyvO0zWPK49rn8gOaKNfNPmgrRzQshfkLvjF1xclJXBj88Aft/0o4rD0LuLzDxHtjygVZ2cDUUbIJrP1MLjopTlu5Wx1oppRRSyuFSypEtP/OllK+2GCBIKV+SUg6VUo6QUk6UUq7uzjF1KU018Mt/3csPTzwdobEaNn/oXr5v0YmPS3Hqsf8nzef4GNilnZzqHKJ9OheUnlnRtUHph3EYTNhMvnhVH3Ipj/ONJbsq2y1QsqsYFOlHs83BpoMV3dK/ohupzIVdX7mWNVZpEqgAtcWwtt087bBruUL0Ru1lUKHoSkr3ub8HNFSAo938lbsWKjqmnKZQnIz0mDrWSYnOoGU9bY/lOAJ+dUYwB7qXe3cuaFhxCmFr0lZ2I4+dSCq3Jg8/L3+PaijHw/5KI9HdsBMC0OwXgaUi26XMpDcR4RNBRoUHmesuQAjBjIFhfLg2p1v6V3QjeqNrIO9hjC33uN6rRV3IQzuHzfN3CkVnMJjclKoATZnN5VjnWeVKoThFUEZIZzBaYNrvXNVVzAFagFhH8bLAxF9psSCHMflByqwuG6biJCd3nSZ64EFatD0ZlRnE+HYuVU+zHQpqDUT6dv1OCECzbziWcvfVwQT/BLaXuicz7CqmpYaxZFcxFXXds9ui6CYCE2DGo65l0aNbleIsgXDmn12/923JkWMOgASVjFXRxUQM0zKYtyV2nLvBMfEeCOk3cWgKRZejRJ+PQJPNTlW9FX+LAbPxKL+mhMlwyyItR4OXj2aAmAM0V60OvBQCkHw6XPeFpvpiMGt9JkzukusAtCRHdWWa/ngHEtkp+hn7f4KoER2quqds93ErrLUnp9pIuLcdYzctYTT5RRBauM2tPDkgiQVZC7l60NV0R4yhv8XI2IQgPl1/kLtmqKzA7SmpacLLIAiweFjh7U10Ok3MI3o01BRq82/YQPBv43I44Ay4eYE2T5v8wD9amxPnzIfwwVBXqq1SH2kHur5C2zXxPYUkZfs55bVN6HSCQO9euF8NXjDudk39qr4MvPy0TObmQE1et3i3psIWN+7ISm5VeZrbYFBCjw5doehJlBHigX1FNby0NJOf95UwLiGY+2elMiT6CFv2eiPEjdd+KnJg/Vuw9SMITNJW3xKncEwN06ZqLevvgeVa3ZAUaK7rGoOhNBPWvAS7v4HIETDzjxA7tvP9KvoOmT/AiGuOWU0i2VeRwfio8Z06XUaFkahu2gUBsFqC0Vkb0DdVY2+TyDPSJ5ImexMFtQVEd3I350icNTSSf/+wj1unJONlUBvFAEXVjXy9OZ+3VmYR6G3kodmDmJoaisnonky116gvg11fa8Hp4YPhjD+7vrwZj7C4U1cG696EVc9r7jMz/6jlHjG1zL3N9ZC5BH78K1jrNIWjYZcrY6QPU1HXzPwdhfx36X4MesGDs9KYOTgCX1MPv+7YGmHfwpZn70iY+ZiWxyPg0qO3qy2GPfNh9X+0pMfj74ChlxxZ4l+h6Meop2w7ymubuO+TzXy7pYCKeiuLdxdx87vrKaxsOHpDuxVW/UebOOpKIX89fHgpHNpx7JPuWwjzfw956zQFjbk3Qe76zl9MY42murXxHU0//8BS+OASKOue7NOKXqC2RFP7CT92/oz82ny89EYCvDrnA7+3zEhMNxohCEGzXxSW0gOuxQgGBqWx7lAX/N84AkmhPkQGmPlua0G3naO/8f22Qp5esIfimib2FdVy2/sb2JpX2dvDaqW5XlO+Wv+GZoxkr4QPLoaSDsQPZS6B+Q9qq87lB+DzW7Rg4cPkrYf/3agtElUXwMKHtXxOij7LiowSHvtqB/mVDeSU1fPrT7ewMbu8ZwfRWKM9053P3p86/uzNWQ3f/0a7H6vytHs744fuH7NC0QsoI6QdOeX17D1U41JWVN1EVlnd0RtWF2g69W2xN0PJ7qO3szbAujfcy7viQVd1UJMMbktTtZZUS3FykLlE29bXHXuVb3f5HuL9Or+1v7fci1i/bjRCgCb/SHw8PLAHBQ9mdcFqoPtUvM9Lj+LlpZnYHf1HKby7qKxv5r3V2W7l67P6kIpYVa6Wq6ktzXVQuvfo7ayNnufe3W36ylzi/v2616Gp9vjHqeh2rHaHR3GJ+dsLe3YgVQc1w6MtHX327pnnXrbtE83YVihOMpQR0g6zUY/Og/eUt9cxXA8MJvAOdi/38j16O2EAfw+uJb6RR2/XEQxmz6oxKi7k5GHP95ovfAfYXrKt05mXG22CgjpDt7pjATT6R+Nd6m6ERPlGIoRgb/kxXjA7QXpMAEaDjnk9/eLSB/Ey6Aj3c/dZD/LpQ8n9DCbP8+yx5jmdAQI8xEf5t8lufjiA3eX7WM/KR4peRy8EUQHuz7zIgM6pAR43nXn2+nm453wi1D2nOClRRkg7ksN8uG1qskvZZaNjGRB2DGPCLxJm/921LGIYRB1DNtVghNN+7Zqx1xIEqWcdx6iPQFASnP5H17IBZ7Sqxij6N7YmyFqhxSMdg2aHlYyKDBL9O7cTklFhJNrH1m1B6Ydp9glD31iDvtE1I7tAMCJsBItzFnfbuYUQXDY6lmcX7cVqd3TbefoD3l4GfjsrDX2blZkwPxPjkzwsuPQWgQnu6lcJUyB86NHb6Q2aglHblztzIAw8p/V4wBmui0v6lvnaoF4I+yI6nWDOaUmY2sRz+ZsNzB7q4cW+OwlKgtMfcy0bcCaEHdttlrRzNXGFwxhMWmZ1vQrhVZx8qLu6HSaDnl9NT2bygBAyi2tJCPFmZFwgfuYOrPwNOl9TWyncqq2gxY6FgLhjt4ubALcugfxN2gMxdhyED+rwmMuqDmJzWAkPSELoWiZfhx1qDmkBbZHDoGinFtgWMwZ8Qjvct6IPs38pBCe7PrCOwN7yvYR7h3c6P8iuUi/i/Lt3FwQAIWgKiMGnNIPq2DEuX6WHpPPG9jfIr80jxrdzSl9HIj0mgCBvIx//ksNNk5O65Rz9hQlJwXz+q0lsy6vC12RgVHwgycdalOlJhNCEGULT4NBOCIjR5l5PK8rtiRsPdyzTEh7qdJpBEzaw9fuIITBnAeRv0AKNI4ZBQAJIeVTBkermauqsdYSaQzHq+9Cu0SnAqLhAvrhrMltzK9HrBCPjAxkU6X/shl2JTgej52jP3sLtmkhC3PiOCRokToZr52r3nMOm7XQnnOaxqrW5ntLafHy8/PDvCu8JhaKHUUaIB4J9TMwYGM6MgeHH19BogcTTtJ/jQQjNrz961HE1q68vZ2nOEp7f8Qb11npuTL2MS1MuIRwDrHsVNr6rGUOz/64pbKjVu5OLnV9CbMeUrjYXbyIpoPMv0ztKvUgN6pk8Go0BMfgU7XYzQrz0RsZHjufjPZ/w+7G/ozvkegGuGR/PPxbu4aKRMb0j89lHMOh1jIoPYlR8H06gavLT5NGPJ0cTQF2Jpi638rA61uPgFwXmNi+t4YO0BZyMxfDFrdBYDRPvgjFzXF23ACklG4s28s91/+RA9QHOSjiLO4ffSUKAklntKYQQDIsJYFhMLyehrC2ETR9ogjBBA+Dsp9zulyMSP0H7OQo5JTt4Y8c7LMxfTpJvPL8fdR/j4qa3LkQqFP0Adbf2Y7Ye2sDD6/5GUX0RNdYaXt71LksO/gCbP4A1L2vBmeUH4NNroHBLbw9X0ZXYmmDvgiOukLXFgWRT8WZSg9I6dUqHhF1lXiQFWDvVT0dpDIrHp2Qf4O4SNTpiFBWNFSw9uKzbzp8Q4sOEpGCeXrCn286h6GX2LtDUhxoqoLYIvr0HDq51r5e/QVMtrMrTAoyX/wO2z3WrllmZyZ1L7mR3xW6a7E18d+A7/rn+nzRYj6GuqDi5aKyGb3+jLRQ1VEDBBk0ts4tEYRoaKvnX5hf55uBimuxN7KnK4FcrHiSzaHOX9K9Q9BTKCOnHrC1a51b2Wdb31FTnuhZKqSVHUpw8ZCzWXLE64FqXWZGJWW8ixNw5P/7sKgM+Rgf+pp5RjbKZ/LAbzZgr8ty+0ws9FySfz1eZX7HukPv/g67iirFx/Li7iLUHyrrtHIpewtqo7Ra3Z68HdaLsVe5lG97Rkhi2Iasqi2aH607hivwVFNYpkYNTiqpcyF3jWtZc12VGyKGagywtXO1SZnVYyarK6pL+FYqeQhkh/ZhIb3d3sTjvKLykh5fEDsQNKPoRmz+EpGkdqrqmcA0Dgwceu+Ix2FpsIrmHdkEO0xCYgO8Rcu0Em4O5PO1yPt3zCa9sfYX9VZlID7smncHby8CcyUk8+L+t1DT27LUruhmdAUIGuJcHJrqXtc2+7qyX4KaA5Gf0c2/q5d/pWCxFP8NoAaO3e7m5a2JTzHoz/l7uffkq5UtFP0MZIf2YCZETiLC0Brp56by4bcj1mIZdDqLNnzZs8HHHmyj6MLXFkLNKUwA6Bs32ZtYdWsfQkGGdPu2GQyYGBPXsi3hjcAJ+hUdO+BnhHc6coXOwGCy8tvV1fv3Tb3hpy4usKViN1dE1sStjEoIYHOXHY1/tQHoy8BX9E70BJvzK9WXRJxTSZrvXTTjNVWRE7wUzHgIvV+MiLTiNydGuWdl/P/b3RPl6MGIUJy9BSTDrSdeywRd0TB2rA0SFpPGHEfe4lE0MG8nAYKV8qehfqMD0fkxyxAjemvECu8t302RvZmBQKgMjx4K0w20/QNFuMPtB1CgI6lx+CEUfYvOHED8ZvDystLVj3aH1RPtE4e/lvkJ7PDTbtXiQ8wYcI2lnF9PkG4G+uRZjbQnWIyjLmPQmJkVNZFLURKqbq8mpzuGn3J/43765XDPoGsZHdix4/2hcPzGBP3+zk4/XHeS6CSrI+KQhdqymTFi0HXRGiBoBoanu9UJT4cZvtdg6WyNEDIXI4W7VQiwh/PW0v7KzdCcVjRUkBiQyJES9GJ5yHFZsCx8C5fvBN1x7DvuEdNkpzko+j1jfaLKrDxJkCmRIyBBCAtXcpOhfKCOkn5MQPoyE8Par3DpNijdmjMc2in6M3aZleZ7+0DGrSiSLshcxMfroKisdYXuJiUgfOz7GHt4JEIL6kGT8CjZTnnbs3Dn+Xv6kh6aTHppOfm0Bn++dS2ZFJtcMvhrRiY1fk0HPr89I5a/zdjEwwo+xiX0oT4aic0QO036ORUiy9nMMwr3DCY8/TmVFxcmHyffE1DI7iNkcwOj4GXQsVa1C0TdR7lgKRX9i97fgHQIhKcesuqN0J032JpICjv3idCzWFJgYGNwz0rztqQ9NISBvI3B8BlCMbzTXDbmOvRV7+WDXB8fdvj3RgRbunJbMnR9sJKesZ3eEFAqFQqE42VBGiELRX5ASVj4HQy46ZlUHks8zPmdS9CR0ncyjYZewMs/C0NDeMUKafCMQdhvmytxjV26HWW/mstRL2V22h0XZnc+yPjIuiEtGxXD9W79QUtPU6f4UCoVCoThVUUaIQtFfyFisyTzGHTvGYU3BGux2W5eoYu0s9cLH6CDc297pvk4IIagPSyMg+5cTam7Sm7gk9WLmHZhHRsW+Tg/njMERTEwK4bo311JZ3zuGmUKhUCgU/R1lhCgU/QGHHX54AoZf7ap85oGq5mo+2/MZZySc2eldEICFB7wZGd67L9u1YYPwK9yCsDWeUPsArwBmJ83m1W2vUW/rvCvVJaNiGBjpx7Vv/EJVg5LuVSgUCoXieFFGSFdzOCFRVX5vj0RxMrH1E01xJX7SUas5kLy5/Q2GhQ0jyiey06etaRasLTAzKuLEXv67CrvJh8bAWAIOrj/hPlICBpAckMwHOz/o9HiEEFwzLp7EUG+ueV3tiPRJ1Fys6G0aq6FkH9QW9fZIFIo+SbcaIUKIOCHEUiHEbiHETiHEbzzUEUKIF4QQmUKIbUKI/iv2ULIP/ncTvDQWXpsKO74Eq/IbV3SShgptF2TMLZohchS+3PcF1U3VnNYuV8GJMn+/D0NCm/Hz6v38GDWRwwnev1zbFTpBpsVOI7Mykw2HTtyYOYwQgusnJDAg3IcrXl1DcU3vGmqKNrSfi7d/oeZiRc9yaDt8eCm8PA5ePx0yfwBH1yZTVSj6O929E2IDHpRSDgYmAvcIIdqLpp8DpLb83AG80s1j6h6sDfDTXyFziXZcXwZf3KLpzysUnWHhoxA3EcKOHt/x08GlrClcw4UDLkIv9J0+bYNN8GWGD1NiGjrdV1fQ7BeBzeRLQN6GE+7DS2fknKRz+WDXB1Q1V3V6TId3REbFB3LZK6vJLa/vdJ+KTmJtgJ/+puZiRe9RXwFf/QryWhY7qvPhk2ugdE/vjkuh6GN0qxEipSyUUm5q+VwD7AZi2lW7CHhfaqwFAoUQ/S+9bG0R7PnOtUxKKMvsnfEoTg72zIMDS2H0DUettjxvOd/u/4bL067Ax3jsJIYd4ZNdvgwItBLl20sB6R6ojhtL6N5FYD/xOIwY32jSw9J5c9sbdFa2FzRD5JJRsZw5OIJL/7uaHfmdN24UnaC2GPZ8615emtHzY1GcmlTnQ9EO1zJ7M5Rn9c54FIo+So/FhAghEoFRQHuJmxigrfZmHu6GCkKIO4QQG4QQG0pKSrptnCeMly94ylbq3XUZUhV9j269L8uz4Nv7YMoDcBTDYmH2Ir7O/IarBl5FkCmwS069q8zIgiwfzknqW/kwmvwiafINIyTjh071Mzl6MpVNVSzMWthFI4OzhkRy/cQErn/zFxbvPNRl/Z4ofX7O7C68fCAw0b1czcV9glPivjT5gcnfvdyikpwqFG3pESNECOELfAHcL6Wsbv+1hyZuy5NSytellGOllGPDwsK6Y5idwycUznsOdG2S0KedDZHDe29Mim6n2+7Lhgr4+EpIvwLCB3usYpcOPt7zMT8d/IlrBl1NkDkIAIeEPWVG/rfHl3/8EsgfVwTzxMpgXtrkz4ID3uTV6JFH2QDIrjLw5KpgLk2txd/U+7Eg7amMn0xQ9mpMVXkn3Ide6LlgwPnMz1rA3vKuc5EYnxTM72YP5NGvtvP8kn04HL33++vzc2Z34RMK57efi2dD1IjeG5PCySlxXwYlwHn/ci0beytEtPdGVyi6ByHEfCFEYG+P41gYjl2lcwghjGgGyEdSyi89VMkD4tocxwIF3T2ubiF5Bty+DMozwRwAEcPAN7y3R6XobzRWwYeXQfhQGHiexyq11jpe2/Yqtc21XDv4Gsx6MyX1Oubt92FxtjcmvSQlyEq4t414Pxt2CZVNOlbmmXlvhx9eesn4qEZGRzSTGtSMv8lBWYOe5QctfJnhy/kD6hjSS8kJj4Xd5ENF4mSi179PzvT7cZyg+1mAVwDnJp/Lf7f8lz+M/wPRvm4bsCfEgDBfnrxoGC8vzWR9djnPXzWSCH9zl/St6CBJM+COZZo7rJqLFb3B4IvgjlQoPwA+4do9aA7o7VEpThGklOf29hg6gpBHWxLtbOdCCOA9oFxKef8R6pwH3AucC0wAXpBSHjUb29ixY+WGDScenKpQHAcdTrTRJfdlVR58dCWEJMO42z3mBNlbvpfXt79BSsAApsVNI6fKxP/2+LL+kJmR4U2Mi2w8ahyHlHCoTs/eci+yq40U1Oqps+rw83KQGtjMtLhGwnorMeFxEJizBmN9BbmT7kAaTvwlf2fZTn7OX8mDYx8g1jfu2A06iN0h+WZLPj/sLuL3swdy9bh4dLrO521p4bg6UnOmogfp2TlToegYXTb5dhVCCB/gf2iL73rgr8A/gM+A01uqXSulzBRChAGvAvEt5fdLKVe1eBq9CIxF8yL6i5TyCyFENjBWSlkqhLge+DXghRYScXdLH2+1afe2lPL5br1gD3T3TshpwA3AdiHElpayR2n5JUopXwXmoxkgmUA9cHM3j0mh6HtICTu/hPkPwZALYcglbnK8Vc1VfLHvS7aWbGFm3FmUNgzl4eU+5FYbmBTTyO/HV2AxHHtRQQiI8rUT5dsA9A3lqxOhMn4iwVkrSfj5RfLHzcHqe2KuHUNDhiKEjn+s+yfXD76OCVET6IrnlV4nuHR0LGMSgnhvdTbvrcnht2emMWtIBPquM0YUCoVC0T85GyiQUp4HIIQIQDNCqqWU44UQNwL/Bs4H/gM8L6VcKYSIBxYBg4E/AVVSyvSWPoLankAIMRi4CjhNSmkVQvwXuA7YCcRIKYe11Avs7ov1RLfuhHQXavVE0YN076qetQH2LYRVL2huWBPvgrBBzq8dSA5U7mdl/kpWF2zF33g6Nc2jWZPvQ6i3g/GRjaSHNWE4VdOOSolv0U4C8jZQFT+BiqQp2CxBx27ngUN1h5iftYBQSwjnDTifwcGDEF0UNielZEN2Bd9tK6C+2c6lo2I4a2gkQ6L9T9QgUTshir6K2glR9EX63MqPECINzZj4H/C9lPLnlh2MmVLKAy3hDIeklCFCiGJcQxXCgEHAMuBqKWVGu76z0XY5rkZb/C9u+coCfIJm1GxA2wiYByyWUvZ4IptujwlRKBRogeZbP4OGck1CtCJbk3CsKwFLEI3J0/nWEcqmjcXUWQupbJaUNUkqm72ptYdQbbsUuBRvvZUU/2rOi84iyKsJHJB/yifjDcMQPoPg/Cy8M17DIPTU+YbSZAnEarRgNflQFpqK1B8rd4qeiWHnkVGRwbOr38YhJWGWUCK8IwgwBzI2YiyhltATHmVkgJnbpiaTVVrLiowSXlyqyXcHWowkh/kQG+RNiK8XARYjPl4G4oItzB4aiThGgkqFQqFQ9D+klPuEEGPQvIGeFkIsPvxV22ot/+qASVJKF/eFlrCHo+0mCOA9KeUjbl8IMQKYDdwDXAncckIX0gn65U6IEKIEyDmOJqFAaTcNp6+grrF7KJVSnt2Rike7L28cYQx872LLgPblJXUOa00zdiw6w3OG2wzf22Yesf8oUYSBvh+r0ZsIwOhhPs4XBtnk4WVeSnnkl3wdou3amb1W2uz10tZFQ9VOYfIx6C1+R1wMyn3x+i2O+ko77vd+h+9LOKE5s6vpD/OTGmPXYD7s4nEsjuO+7A/XfTTU+HuXUGDP8cyZPYEQIhotZrpRCHExMAcYCbwqpXymJZbjKinlBUKIj4HNUsr/a2k7Ukq5RQjxDNr/uftbyoOklBVtdkLCgW/Q3LGKhRDBgB9QBzRLKauFECOBd6WUI3vq2g/TL42Q40UIsUFKOba3x9GdqGs8degvv4f+MM7+MEboP+M8Ev1h/GqMXUN3jLE/XPfRUOPvXfrq+IUQs4H/AxyAFbgL+Bx4B213RAdc0xKYHgq8jBYHYgBWSCl/1RKY/jIwBrCjBaZ/2S4w/SrgkZb+rGg7Hw0t5znsc/yIlHJBD1y2C8odS6FQKBQKhUKh6EGklIvQYkKctOzMvyyl/Eu7uqVoAebt+6gFbvJQntjm82doilvtGX0i4+5KTtVwVoVCoVAoFAqFQtFLnCo7Ia/39gB6AHWNpw795ffQH8bZH8YI/WecR6I/jF+NsWvojjH2h+s+Gmr8vUu/GX/bHYxTgVMiJkShUCgUCoVCoVD0HZQ7lkKhUCgUCoVCoehRlBGiUCgUCoVCoVAoehRlhCgUCoVCoVAoFIoeRRkhCoVCoVAoFApFP0UIMacl+WG/QhkhCoVCoVAoFApF/2UO0O+MkH6pjnX22WfLhQsX9vYwFKcGoqMV1X2p6EE6fF+CujcVPYqaMxV9keOaM4+XxIfnXQv8HYgHDgKPZj9z3sed6VMI4QP8D4gF9MBfgUzgOcAXKEUzPk4D3gXy0TKhTwImA8+ipeJYD9wlpWwSQjwDXAjYgMVSyt8JIS4A/gh4AWXAdVLKos6MvaP0y52Q0tLS3h6CQuGGui8VfRV1byr6Iuq+VJwMtBggbwAJaMZOAvBGS3lnOBsokFKOkFIOAxYCLwKXSynHAG8DT0kpPwc2oBkPIwGJZpRcJaVMRzNE7hJCBAOXAEOllMOBv7WcZyUwUUo5CvgUeKiT4+4wfcIIEUIMFEJsafNTLYS4v7fHpVAoFAqFQqFQHIW/A97tyrxbyjvDduBMIcQ/hBBTgThgGLBECLEFbfci1kO7gUCWlHJfy/F7wDSgGmgE3hRCXArUt3wfCywSQmwHfg8M7eS4O0yfyJgupdwLjAQQQujRtpS+6s0xKRQKhUKhUCgUxyD+OMs7hJRynxBiDHAu8DSwBNgppZx0jKYeXc+klDYhxHjgDOBq4F5gJtruynNSym+FEDOAJzoz7uOhTxgh7TgD2C+lzOntgSi6n8rGSvZU7KG8sZx4v3gGBg3EqDf29rBOSewOOxmVGWRVZRHgFUBacBqhltDeHpZCoVAo+hFFdUXsLd9Lg72BAYEDSAlM6e0hdTcH0VywPJWfMC1qV+VSyg+FELXAHUCYEGKSlHKNEMIIpEkpdwI1gF9L0z1AohAiRUqZCdwALBdC+ALeUsr5Qoi1aPElAAFoi/8AN3VmzMdLXzRCrgY+aV8ohLgD7Q9AfHynjEtFH6GqqYpnNzzLN/u/AUAgeGbaM5ybdG4vj6zjnEz35drCtdz7473YpA2AqdFT+ctpfyHMO6yXR6Y4EU6me1Nx8qDuy5Ob/Jp8Hlj2ALvKdwFg1pt546w3GBk+sncH1r08ihYT0tYlq76lvDOkA/8nhHAAVuAutIDyF4QQAWjv8P8GdqLFgLwqhDgcmH4zMFcIcTgw/VUgGPhGCGFG2y35bct5nmipmw+sBZI6Oe4O06fUsYQQXkABWtDMESPzx44dKzds2NBzA1N0CxsObeDmRTe7lPl7+TP3grlE+/YZpbkOK2r05/uyorGCa+ddS15tnkv5y2e8zLTYab00KsVROC6ll/58byr6HafEnKnwzLwD83j454ddyiZGTuTFM17EbDD30qiAfqiOdSrQ13ZCzgE29ZQ0mKJ3qWyqdCurbq6mzlrX84M5xam31pNfm+9W7ulvpFAAbMwpZ1hMACaDvreHolAo+giFdYVuZQeqD1Bvre9tI6RbaTE4lNFxnPQJdaw2XIMHVyzFyUmCfwIGnQGDMODv5Q9Aemg6Ed4RvTyyU49QSyizEma5lAkEif6JvTMgRZ+mutHKZa+s4fONeceurFAoThmGhQ5zKzs/+XyCzEG9MBpFX6fP7IQIIbyBWcCdvT0WRc8wIHAAr575KluKt1DaUEpiQCJjwsfgb/Lv7aGdcpgMJu4ddS9Wh5WluUsJMYfw6IRHGRw82KVeZmUmm4o2UWetY3TEaIaGDMWg6zPTiJN9FfvYVLSJZnszo8JHMTR0KDrR19Zc+i97CmsA2J5XBRN6eTAKhaLLqbfWs6N0B1tKthDhE8Ho8NHE+cW51SuoKWBLyRZya3IZFjqMtKA0Hp/4OM9vfJ46Wx0XJl/IFWlXIES3ekMp+il95u1BSlkPhPT2OBQ9R251Lv/e9G92lO5wlt014i5SglL65IvtyU5SQBL/mPYPiuuLsRgshHuHu3yfWZHJzYtudrpo6YSO1858jYnRE3thtEdmd/lubll4C7XWWgAMwsCbs99kTMSYXh7ZycPB8np8TQZyy+uPXVmhUPQ7fsj5gcdWPeY8TvZP5pVZr7jEa5bUl/DQzw+xtWSrs+x3Y3/HjUNuZErMFJrtzUT5RuGl9+rRsSv6D2ppUNErFNYWsqt8l4sBAvDOjnfIqMjopVEpLAYLCf4JbgYIwLpD61xiRBzSwWvbXqPR1uhSr6C2gO0l2ymoLeju4XpkRe4KpwECYJM23t/5PjaHrVfGczJyqKqBlHAfiqqbensoCoWiiymuL+bZDc+6lB2oPsCe8j0U1hWyvWQ7+TX5ZFRkuBggAC9veZm82jyifKNICEhQBojiqCgjRNHjrClYw1XfX0V1U7Xbd432Rprtzb0wKsWxqGqqcisrayzD6rA6j1fnr+bq76/m2vnXcuX3V/Jz3s/0tAJfWUOZW1lpQyl2ae/RcZzMFFU3ER/sQ3m9+r+qUJxsWO1Waqw1buXljeUu83tJQ4lbnQZbg3qGKzqMMkIUPUpudS4PLnuQiqYKAswB+Bn9XL6fEjOFBH9POX8Uvc34qPGIdiqH1w++Hj8v7W+YW5PLg8u1vy1oRsuDyx/kYHWn8jUdNzPjZ7qVXTP4Gkx6U4+O42SmtLaJ2CALVfVWHI6+I/OuUCg6T7hPOFemXelS5qXzoqqpivLGckBTssyrzcPX6OtSb1b8rL4ksa9ohxDiSSHEmSfQboYQ4vuuHo8yQhQ9SnFDsXOF5bn1z/G3KX9jcvRkIrwjuDLtSn496tcEmgN7d5AKj6SHpvPSGS8xNGQosX6xPDbhMc6IP8P5fXFdsYsbFGirYofqD/XoOEeGj+Q/p/+HgUEDSfBP4MnJTzI1emqPjuFkp7yumQCLEbNRR22zcnNTKE4mjDojc4bO4a4RdxHpE8nEyIm8MPMFPtz9oUu9j3Z9xL9m/IvpsdOJ8I5gztA5/HbMb7EYLL00cgWA0PD4fi+lfFxK+UMPjKFDgb0q+lfRowSbgjHpTTTZmyisL+Q3S3/DdYOu44HRDzAgaIAKSO/DeOm9mBY7jTHhY7A6rG7GYpA5CC+dF82O1q14g85AiLln9SbMBjMz42cyLnIcDukgwBTQo+c/FahqsOJnNuJrNlBZZ8XfbOztISkUii4kyjeKu0fezTWDrsFisHCo7pBbDq96Wz2hllCenf4sddY6gsxBp64K4RMBbskKeaKqU3lDhBD/AHKklP9tOX4CqEHbQLgSMAFfSSn/LIRIBBYAS9Eypl8shPgLMBaQwNtSyueFEO8C30spPxdCjAP+A/gATcAZaJnZX2lpZwMekFIubTeuYOBtIBktM/wdUsptLeOLBhKBUuDaY13jKXq3KHqLhIAEHp/0OHqhJTjTCR2pQakkByW7GCCl9aX8UvgLawrWUFSvclf2JXy8fDzuViX4J/DnSX92+dv+ccIfSQjoefe6soYydpfvZlfZLg7V9exOzKlAVYMVHy89viYD1Y3WYzdQKBT9jpyqHHaU7mBvxV5CzCE8MekJDC0L3Dqh45EJj5Dkn4TZYCbEEnKqGyBvAAlomdkTgDdayjvDp8BVbY6vBEqAVGA8MBIYI4SY1vL9QOB9KeUoIBSIkVIOk1KmA++07VgI4QV8BvxGSjkCOBNoAO4BaGlzDfCeEKJ9lsm/AJullMOBR4H323w3BrhIStmha1fLzooeRSd0nJN0DoOCB1FUV0S4dzjJAckYda0rqQerD/L75b9nV/kuABL9E/nP6f8hOTC5t4at6AB6nV7724Yc+W/bE+TV5PHIz4+wpWQLALG+sbw480VSglJ6dBwnM9WNVnxMBry99FQ3KCNEoTjZ2FS0ibt+uIt6mybDfUXaFdw78l7+d8H/OFR3iDDvMG1+16tdULQdEO92Zd4t5Se8GyKl3CyECBdCRANhQAUwHDgL2NxSzRfNKDmItmuytqX8AJAshHgRmAcsbtf9QKBQSrm+5VzVAEKIKcCLLWV7hBA5QFq7tlOAy1rq/CSECBFCHHY5+FZK2dDRazxFzVZFd1PdVO1RTQk0f9O0oDSmxk5lYPBAt0lsRd4KpwECkF2dzbysed06XsWJ02BroLyhHId0YNQf/W/bE6wpWOM0QADyavP4IuOLHlfpOlmxOyQNzXYsXnosXgZqmlRMiELR36hprqGysdLjd1WNVfxt7d+cBgjA3H1z2Vuxl9SgVKbGTmVQ8CAlv9tK/HGWHw+fA5ej7Yh8irbT8rSUcmTLT4qU8q2Wuk5/OSllBTACWIa2u/Fmu34FmptWezqSVdJTncN91Xn47ogoI0TRpdQ21zLvwDyun38918+/nu/3f09tc+2xG7Zhc/Fmt7JfCn/B7lASq32NrcVb+c1Pv+GK76/g3xv/TW51bm8PyS33DMD6Q+tpsqucFl1BbaMNi1GPTggsRj21jcoIUSj6C022JpblLuPmhTdzzbxr+HTPp5Q3lLvUqbHWkFHpnq/LkySvAtB2IY6n/Hj4FLgazRD5HFgE3CKE8AUQQsQIIdwSewkhQgGdlPIL4E/A6HZV9gDRLXEhCCH8WoLJVwDXtZSloRlSe9u1bVtnBlB6eCfleFFGiKJLWX9oPQ///DBZ1VlkV2fzyMpHWHdo3XH1MTXWXcnorISz0Ov0XTVMRRdwoPIAty+5nTWFayiuL+adne/wytZXaLL17sv+hKgJbmVnJZ6F2dDerVVxItQ0WfH20jx5zQYdtWonRKHoN2wv3c59P93H3oq95NXm8dQvT7E01yXumCBzEOMjx7u1jfWN7alh9jceRQvQbkt9S3mnkFLuBPyAfClloZRyMZqL1xohxHY0w8TPQ9MYYJkQYgvwLvBIu36b0XZXXhRCbAWWAGbgv4C+pe/PgDlSyvYP9SeAsUKIbcAzwE0nen3KCFF0Kd/s/8at7Mt9Xx5XH5OiJnFJyiXOnBSzEmZxRsIZx2il6GkyKzNpsLm6fs7LmtfjkrztGRc5jqvSrnIGSc6IncE5ief06phOJmqbbHibtAUBk1EZIQpFf2JVwSq3so92f0Rdc6sXjY/Rh4fGPcSAwAEAmPQmHhn/CIOCB/XYOPsVmgrW7UAOmltSDnB7Z9WxDiOlTJdSnt7m+D8tZelSyklSyv1Symwp5bA2dbZKKUe3cdta0FI+R0r5ecvn9VLKiVLKES3/1kopG1vqpEspRx1WxpJSLpNSnt/yuVxKeZGUcnhLu20t5U9IKZ89nmtTgemKLiXc4rYrSLiPe9nRiPCJ4NEJj3L94OuRSOL84vA2to/5UvQ2nrTgvQ3evS6zHOYdxu/H/Z6rBl2FXdqJ84vDx+jTq2M6mahttOFtbDFCDHrqlBGiUPQbgkxBbmWhllAMetd5e2DwQN6Z/Q4FtQX4GH2I948/ddWvOoJmcHSJ0XEqoYwQRZdRUFvAucnnsr9yP+uKNBessRFjuXDAhRTUFhwxi2pJQwm1zbWEWcLw9dKyr5oNZtKC2wsyKHobKSUFtQXYHDbSAtMYGjKUnWU7nd8/MPYBfAw+ZFVlEWgKJMjs/sDrCuqsdZTUl+Bt9Cbc293INRlMpAaldsu5T3VqmmyYvTQjxOKlVzshCkU/YlL0JAJMAU7hGL3Qc1v6bejQkVOdg0EYiPaNRghBkDnohOfwgtoCrA4rkd6RmAwmj3UabY0cqjuEyWAiyifqhK9J0X9RRoii09RZ65h3YB7Pb3yeels9sxNm88LpLwCwKHsRNy28CW+DN/ePuZ/zks5zGhp2h53VBav5y5q/UFRfxOjw0Tw24TFlfPRRqpur+W7/d7yw6QWa7E1cNOAinjztSTIrMimoK2B46HCMOiM3L7qZzMpMkgKS+MukvzAqYlSXjiOzIpOn1z3NukPrCLWE8qeJf2Jq7NQelwI+ValvsmNu2QkxG/SU1qmAf4Wiv5AalMq7Z7/LluIt1FvrGRk+klBLKP+3/v+Yu28uRr2RX434FZelXnZCiV5rm2uZnzXf+T5wXtJ53D3ybmL9XONJcqpz+PfGf/PjwR/xN/nz0NiHVOzeKYjaW1N0mh2lO/jr2r8iEIRaQlmQvYD9lfvZUrKFeVnzcEgHtdZa/rb2b+woa1Uu2l+1n18v/bUzGeGm4k38ec2fqW46IZEFRTezrXgbz6x7hnpbPXZp58vML/np4E+cm3wut6XfRpx/HL9d9lsyKzMByKrK4r6l95Ffk99lY6iz1jkNEIDShlLtnBWZXXYOxdGpa7JhNmqPDrNRR32TUq1TKPoTKYEpXJ52OTcOvZHhYcNZkrOET/Z+gk3aaLA18PzG59lUtOmE+t5Rpr0P1FprcUgH3x34jrl75+KQDmcdq93K29vf5oeDPyCRVDVV8diqx9hVtusoPStORvrETogQIhBNw3gYWlDPLVLKNb06qJOEisYKNhdvZuOhjQwIGsD4yPFuKxKdZV/FPu4ZeQ/VzdXUNteS6J+ITdqYd8A9t8f2ku1MjJoIaEkJbQ5XV44dpTsoqi/C3+TfpWNUdJ5Nxe4PpW/3f8s1g64hwBRAQW0BZY1lLt9XNVWRX5tPjF8MoD18tpduZ3XBaryN3kyOmoxO6FhVsIo6ax2ToyeTHpp+xPwiJfUlbmprDukgpzqHwSGDu+hKFUejrtmG2dAmJqRZuWMpFP2JveV7WV2wmjprHafHnc63+791q7MqfxWnx5/uofXR8SSR/n3W99w09CaCLcEAlDWWsSB7gVu9A1UHGB3RXklWcTLTJ4wQ4D/AQinl5S2p5FUUchdgc9j4ePfHvLrtVWdZemg6/zn9P4R5h3XZeZIDknn454epbKp0lj077VkGBAxw7nIcpm1cSKAp0K2vAFOACiLuo8T5xbmVpQWlOQPU/b380Qs9dtm6Mq4TOpct/Y1FG7ljyR3IlrxGrxle41cjfsVzG58D4PVtr/P6rNeZGD3R4xi8jd6EmEPcjJ1Ac2Cnrk3Rceqb7XgZtJ0Qk1FHQ7PaCVEo+gt7y/dy08KbqLNqaljL85aTGpjKvop9LvUOK2MdL55iOwYEDMBibBUy8TZ4k+CfwJ7yPS71fI2+J3RORf+l192xhBD+wDTgLdC0i6WUlb06qJOE3Jpc3tzhmiRze+l2p7vMsShvKGdr8Vb2lu+l0dbo9r3VYWV/5X4OVh90MUBAe5m8c8SdLgpKQ4KHMDJspPM4LSiNS1IucR4LBI9NeOyIAeyK3mVs5FhSA1uDvb0N3tw67FZn1txE/0TuH32/S5t7Rt5Don8iAE32Jt7a/hbnJJ3Dr0b8irtG3MWw0GEcqjvkNEglkje3v3nExILh3uE8PulxF5WWsxPPZmDgwK67UMVRqWm0qp0QhaKfcngH5DB7yvcwPmo8/l6t3gfxfvFMip7ksX1uTS6bizaTU5WDlO4Jt0eGjeSiARdx14i7+NVwLbbk7pF3u7wL2Bw2Lk+93CWOLz003RkvqjgyQohoIcTnJ9BufovX0dHqPCmEOPOEB3cC9IWdkGSgBHhHCDEC2Aj8RkrpkvpdCHEHcAdAfHx8jw+yP2J32N3cnQCa7c3HbJtZkckDyx8gqyoLgeCGITdwW/ptTqWMRlsjX2R8wUtbXuKy1Mvc2tdaa0kOSOaT8z5hf+V+Te0qKI1In0hnHX+TPw+MeYDzks+jvLGceL/4fqdodCrdl3F+cfz3zP+yr3wfTY4mBgQMIDkw2fm9QWdgYPBAfjP6NzTYGrAYLAwOGux0rbI77EyPm853+79jftZ8AGbGzyTBPwGTvlU9paa5BrvDDkfITTk1diqfnPcJB6sPEmgOZGDgQIIs3aPC1Z/prnuzrsmOqSUmxGRQOyGK4+NUmjP7Im0NkMN8mfEl7539HtnV2Rh0BtKC0jwuBv6c9zMPrXiIWmstFoOFv572V86MP9MlkbDZYMZisPDq1leRSFICU7hh8A0u/dikjY/3fMzt6bdjl3YMOgP5tfmU1pd2/QWfZEgpC9Cyp7sghDBIKY+4IiSlPLcDfT/eyeEdN33BCDGgpZO/T0r5ixDiP8DDaGnmnUgpXwdeBxg7dqy7+a1wI8Yvhlnxs1hycImzLNgc7NxmlVJic9jc/O8bbA28se0NsqqytHpI3t/1PhOjJjqzme+r2Mcz654BNN1xg9AmLj8vP7aUbGHO0DkEmgMJNAcedVs30BzoMcN1f+FkuC+tdusRYzDaE+kT6WJItuVgzUHuX3o/SQFJTIyayE8Hf+K1ra8x94K5JAYkYjaYya3NZVd5a/DhTwd/YmLkRMoby51lNwy94ah5YYw6I0NChjAkZEgHr/DUpLvuzbpmG6G+mtFoNupotDqO0UKhaOVkmDP7Os32ZucOdXsmR0/m9W2vO11iAa5Mu5KUoBRSglKO2GdeTR5/WPEHaq21gPae8MjPj5B6QSpJAUnOd4ntpdv5dO+nznaZlZm8u+tdHp/4uPM5E2YJ4/zk83lh8wvOekadkWsHXdup6+5N0t9Lvxb4OxAPHAQe3X7T9k7lDRFC/APIkVL+t+X4CaAGuFlKOUwIMQc4Dy3TuY8Q4ny07OiDgN1AInCPlHKDECIbGAv4AguAlcBkIB+4SErZIIR4F/heSvm5EGIcWqiED9AEnAGEAB+0lAHcK6Vc3Zlr7AtGSB6QJ6X8peX4czQjRNFJLAYLvx3zWwYEDmBh9kKGhw7nhiE3EOsXy+6y3czdN5c95Xu4KOUiTo87HX8vf9YfWs/+yv2sKnTPqppVleU0QgpqC5zlP+T8wD+n/5Pv939PeWM5D417iNOiT+ux61ScGLk1uSzIWsDS3KVMjp7M+UnnkxSYdML9ldSX8MTkJ9hRuoO1hWsZFT6Km4bcRFF9EYkBidRZ61hT4K43kVmVyRnxZ5BVlcWcoXOYGjO1M5el6Gbqm+yYAw/vhOhpsKqdEIWiL5Bdlc28rHn8nPczM+JmcE7SOST4J7jUGRo8lOdnPM97O9+jzlbHlWlXdmghsKS+hBprjUuZTugoaSjhs72fsa10G5emXEppg/tuxsr8lVQ3VxNiCQFACMHFKRfj6+XLZ3s/I8Y3hluH3dpvM7K3GCBv0BrPnAC8kf5eOp00RD4F/g38t+X4SuBXwM1t6kwChkspy4UQvwMqpJTDhRDDgC1H6DcVuEZKebsQ4n/AZcCHh79sic3+DLhKSrm+JWyiASgGZkkpG4UQqcAnaIbNCdPrRoiU8pAQIlcIMVBKuRfN2lI6bV1EnH8c94y6hxuH3IjZaMaoM5Jdlc1ti2+julmTwt1eup3C2kLGRo7l7h/vZmzEWIaGDGV1gauB23Yyi/CJcH4+I+EM/rDiD1gdVgC2lGzhL5P+wqV+l/bAFSpOhOqmap5c8yRrC9cCmqLJstxlvHbma4R6h55Qn0GmIP614V9OGeadZTvZcGgDf5/6d0CLIZkUNcm5w3aYkWEjmZUwC4d0HHUHRNE3qGu2YTocE2LUKSNEoegDlDeW84ef/+CUud1ZtpM1BWt44fQXCDC3ioPsqdjDQyseYkzkGILMQTy38TkCzAGc7XP2UfsPsYTgbfCm3lbvLLt+0PX8YcUfnEIhu8p28fA49zXk8ZHj8fPycykL8w7jmkHXcGHyhRj1xiPu3PQT/o67oJJ3S/kJGyFSys1CiHAhRDQQBlSg7bK0ZYmU8rArwRS03QuklDuEENuO0HWWlHJLy+eNaDsmbRkIFEop17f0VQ0ghPABXhJCjATsQKeTuvW6EdLCfcBHLdbXAVytPEUX4GdqnQAyKjKcBshhNhVt4mD1Qf4+5e802ZvwNngzJGQI7+x4B7u0c+GAC/HSe7G5eDMpgSmkBaVx38j7eHP7m1Q3VTsNkMO8seMNZibM9KiApeh9DtYcdBogh9lXsY/s6uwTNkIK6wpd8sCA9sArqC0gNSgVvU7PlQOvZE3BGrKqNUNkRuwM0oLSWJ63HKvdSkpQSr9dDTtVaGi2O/OEeOl12OwOHA6JTid6eWQKxalLTlWOW56NTcWbyK7OZoR5hLNsdcFqmh3NLrvS7+x4h2kx0466CBTnF8ez055lT8UeGu2NmPQmkvyTeGvnW846Dulge+l2zk061xn3F+0T7SJg0pasqiyyq7LxMfqQGpR6wtnZ+wBHCm7qiqCnz9FiQCLRdkba0zbIp6OTcFvlFztgafe9ADy5Sv4WKAJGoAlbuSsWHSd9wghpscg6taWj6Dg6nQdRNAGXpF7Ck2uf5FDdIQAS/BJ4+YyXnVK/dyy5A4DrBl2n7a4MvZHpcdNZf2i9W3deOi90vS++pjgCeuE56rut6tRx96nz3Gfbc1kdVqbETGF20mwEguEhw3l05aNOechgczDPzXiOMRFjTngciu6lvtmOqSVjuhACL4OORpsdb68+8ThRKE5JPD7XcZ+X2ypSHcakMx1z7pdIShpLeHHzi854kntH3svAoIHsrdjrrOdr9MWoM3L3iLtxSAf1tnq3RUqAzcWbuXPJnTTYGgCYETeDxyc+3qXpA3qQg2guWJ7KO8unaK5eocB0wHSUuivRXLaWCiGGAOkneM49QLQQYlyLO5YfmjtWAFr4hEMIcRNHlI/pOOqpcZJR2lCKDp0zKRBAg7WBwrpCAs2B6IWeGJ8Ybht6G2/ubJXvvSLtClbmr3QaIAA5NTlsLNrIpqJNbCze6Cz/aM9HzEqcxZiIMQwMHogQAh+jj4vqxt0j7lYJB/sw8f7xnJN0DguyWhNGjYsYR7J/MsX1xZj15iP+/QprC2myN5EYkAhAbXMtddY6kgOSOS36NFYVtMYTjY8cT2pQKkV1RZgNZj7d8ylfZHwBaO5b5qFmF3368sZyPtvzGQMCBtBkbyLEEoJBp6apvkSD1Y6XvvWFxWTQU9+sjBCForspqS/BqDd69DBI8k9ym39nxs10SqQfZlL0JF7d9qqLDPptw2/DbDAf9dw5VTk8tfYpRkeMZmDQQLKqsnhl6ys8MPoB1hevJ9onmi3FW0gMSOTpdU+7tq3O4dnpz1JSX+LMHfXs+medBgjAstxlXJZ6GTO8Z3T499GHeBTXmBCA+pbyTiGl3NliBORLKQuFEIlHqf5f4L0WN6zNwDag6gTO2SyEuAp4UQhhQTNAzmzp/wshxBXAUlx3YU4I9dQ4SahorGD+gfm8sf0NjHoj9426j5lxM8muzubdHe+ysmAlqUGpXJpyKa9sfYWUwBTemPUGC7IWMCV2ChMjJ/L5Pnfp6b3le4nyjdLCkdpQ3tCqZpQWlMY7s9/hx4M/UlJfwlmJZzEqfFR3X7KiE/gYfXhgzANMjprMmsI1jI4YzYjQEby2/TW+yfyGWN9YHhj7AOOjxjtXyKqbqlmau5RXt71KXXMdl6Vdxoy4GTyz7hmyq7I5J+kc7h15L5OjJ7O5eDMjwkYwJmIMb+14i+/3f0+cXxyXpV3GyvyVWrC6fyLZ1dluY9tbsZfXt73O15lfc/6A87lh8A3E+bsnSlT0Dm3dsUCT6W1UcSEKRbdRXF/M1xlf8+HuD/Hz8uO3Y37LlJgpLoaDv8mfP036E2sK1rD+0HomRE1gUtQkt9wbAwIH8Nz05/gp9yfqrHXMiJvRoTxLlU2V3DvqXtYWruWb/d8wOHgwj054lEifSBblLGL9ofWcEXcGEd4Rbm1Hho3ko90f8dHuj9AJHY9NeIyMygy3eiX1JSfw2+l9tt+0/eP099Khi9WxDiOlTG/zORsY1vL5XTQ1rMM0Ate3BI4PAH4EclrqJrbUKT3cvqX82Taf57T5vB5onzU4Axje5viRE7qgNigj5CTh5/yfeWb9M87jx1Y+xtuz3+alTS+xqWQTAFuKt5BRkcF1g6/j9W2vk1uTyytnvkKsXywA02Ons6l4k0u/k2Mms+zgMpcyndA52xxmcMhgBocM7oYrU3QXkT6RXJx6MRenXozVbuXvv/ydzzM0Q3R3xW7u+uEuPjrvI6cU7saijfxx1R+d7d/c/iYmvYna5lpqrbXM3TeXqqYqnpryFDcOvZFmezNPrH6C7w58B8Cu8l3sW7ePO4ffyctbXmZn2U4uGHABX2V+5TKucZHjWJyzmBprDZ/s+YTa5lqemPxEfw9cPGlosNqdgemgBacrI0Sh6D4WZi3kxS0vAlDRVMFvl/2Wt2e/zbjIcS71YnxjuDztci5Pc0sj4WRLyRbu+ekeIn0i8dH7sDB7IY9NeIyrB1191DEEmYP4MuNL58LRhqINTI6ezLMbWnc0vj3wLWWNZS47Mv5e/vh6+fLUL085+3pz+5tMi5nGopxFLuc4vLveH2kxOLrE6OgE3miuWEa0uI67pJTHTgzXiyin/ZMAq93K3L1z3cpza3KdBgjAmfFncsuwW/Ax+PDrUb8mzi+OveV72Vy8mSZbEw7pYHbCbHRCh17oOT/5fJrtzdw76l5SAjX9cH8vf/457Z/OY8XJQXF9MV9nfu1SZpM2DlQdcB5vKNrg1m7egXlcmtKqgpbgn8Dy3OW8u/NdNhZtZF7WPNc+HTbMem31zoGDIHMQNwy+welyNTN+Jia9iaL6otZzZM3jUP0hFH2DRqsdL4OrO1ZDs8oVolB0B1VNVS55Nw6z4ZD7fNwRNh7ayD+n/ZObh97MJWmX8Nz051hbsJba5tqjj6O5ym3nusne5OJSBbCqYBWXpV6Gl05bNPr1qF+zKNvV2NhWuo0pMVMYF6EZURaDhUfGP6JyP3USKWWNlHKslHKElHK4lHLBsVv1Lmon5CRAr9MT5xfHlpItLuXeBm/MejON9kbGR45HL/S8uPlF5/eXp16OQWfgxgU38tLMl8ivzedQ/SFuT78diWRl/koMOgNz981lRqwWNBbhE+Exk6qif2MymAgyB1HS4Lod7m1odXENMYe4tQu1hDrlGS8acBFVTVX8bsXvAJgzdA4BXgFUNFW4tIn1i+WrC79y3rdTY6ZyTtI52KWdZnszty6+1aV+oCnQabgoeheHQ9Jsc7QzQnTUNx8xUa9CoegEJr2JKJ8ocmtyXcpDLSemYjg6YjSPrnzUmc/DqDPy7PRnj7nTfDh43SFbFxw8CZx4G7wZFDyILy/8kmZHM3G+cWwu3uxWb0/5Hl6Y+QIFdQWY9Wbi/OIQQinsnWqonZCTAJ3QcfWgq50vagLB7ITZRPhE8NSUp4j2iWZsxFi3rc8vM7+krEF7gfzTqj9xwYAL2Fexj9e2vcbr217nYPVBEv0TKawrpKyxjOrmakSHFeAU/YlQSygPj3fVdx8SPITBwa0uduMixxFmaVUuMegMXDf4Oj7a8xEAp8Wcxtx9rTtyeqHnhiE3uPQ5KHgQ/iZ/UoJSSApIwqAzYDKYSA9LZ2T4SBL8E5gWM40bh9zIHcPvYFbCLP4w7g+Ee4d3x2UrjpNGm7YLomvzsuCl19FoUzshCkV3YDaY+dWIX2EQrWvGEd4RjI08MUHRHaU7XBIKWh1WPt37Kc22o3vtGPVGrki7gktSLuH29Nu5cuCV+Hr5uiU6fGDsA8T4xSCEQAiBRHJJ6iVYDK0qsH5GP85MOBNfL1/SgtKI949XBsgpitoJOUkYHjacD879gN1luwn3Dufdne9y44Ib8TZ4c/fIu4nxiXFr45AOCusKAW2rNdw7nA/P/ZDtJdsprtci0d/d8S4PjHmArzO/5t6f7iXQFMjjEx9nRvwMj1J/iv7L9NjpvH/2+2RUZhBoCmRo6FBNlKCF9LB0Xpj5AjvLdtJka2Jg8EAS/RP5v2n/R1lDGUad0SndCJpxHGrWjJuS+hK8jd7E+cVR31zv6fSAtusxK3EW/7f+/6hurmZ46HAGBA7o1utWdBwtKN119dPLoKOhWcWEKBTdxZiIMXx47ofsKd+DxWBhaMhQEgI8KcIem+KGYvey+mKaHE344uuhhUa9rZ700HRe3fYqeTV5RHhHMGzkMO4beR/XDrqW4vpiBgQOIMk/ifd3vs/LW16m0d7I6XGn8+DYB3n1zFfZXb4bgWBIyBBGho88ofErTi6UEXISMSh4EAMCBvDE6ieciejqbfU8u+FZXj3zVULMIU7XGYB4v3jnhDQ7YTZhljBMBhOpgam8suUVXtn2CrMTZ/N15tdOGdXKpkp+t+J3fHbeZwwKUUnlTiZMBhOjIkYxKuLIymbDQocxLHSYS1mEj6aGkl2VTbRPNAV1BQDUW+v55sA3bCzaiEEYsEnNZeeNWW8csf99Ffv406o/OY+3lW7jXxv+xb9P/7fKpt4HaGgXDwKaEdJkU0aIQtFd6ISOoaFDGRo6tNN9TYycyKd7XGNMzk8+nxCLu7ttW3yNvjy/8XnnO0RRfRFPr3ua989+n5nxM531VuWv4l8b/+U8Xpq7lFjfWB4c+yCjI0Z3evyKkwvljnWSUdZYxpKDS9zK82vzeXb6s4yLHIfFYGFazDRuHnozP+T8wBVpV3DvqHsxGbQcOEIILk29lNuG3caAgAEueRxA20Fp75+qOPlotjez4dAGnvnlGf6z6T9sL9mOlJ6SqGokBiTyzNRnmBg1EYvBQrx/PBuLtPwyhw0Q0O7Fv//yd17c/CI7Sl0zrOfU5Lj1u6ZwjYv7gKL3aLS6yvMCGPU66tVOiELRLxgTOYY/T/ozUT5RBJgCuD39dmbGzWTDoQ08/cvTvLDpBXaU7nCb6ysbK10WMQEabA1uMX/ts7YDLMxeSGVTZZdfi6L/o3ZCTjL8jH6kBqayrXSbS3mgKZCXNr+EyWDi8rTL2Ve+j4qmCj469yNi/GLcXKsifSO5b/R9ZFdl89nez9wmnyBLULdfi6J32VS0iTuW3OF0sXp/5/u8e/a7pIcdOQnrqIhRPDv9WUobSjHrzXyw6wPyavNc6pQ2lPLJnk8AeG/ne7x39nvOFT5Pwe+xvrH4Go/sJqDoORqaHS7yvKDyhCgU/YlAUyCXp13OxKiJ2Bw2EgMSWV2wmjuX3Oms897O93jvnPdcdr0DzYF46bxodrTGjggEQWbXdwFP8XtpQWn4GH264WoU/R21E3KS4ePlw+/G/s4lCGxqzFQCTYFsLN7I6oLVfLDrA2qsNdgcNjIrMymua/URrWysZHPxZrYUb6G6qZrkwGT+POnPLioYVw+8mrTAtB69LkXPYrPbeHfnuy4xHs2OZpblLTt6O4eNg9UHOVB5gLLGMp6e+rSLgTszfiZ7yvc4j5vsTS4ZfgcFD+KC5Aucx0adkccnPU6wJbgLrkrRWbQcIa6PDYNO0GhVgekKRX8i1i+WxIBEmu3NvL39bZfvmh3NrClYQ2FtIesK17G7bDcRlggemeCam+7+0feT5J/kUubn5cfw0NZ8dr5GX85MONPFeFEoDqN2Qk5CRkWM4tPzPiW7Ohsfow+pQalsKd7i/H5c5DiSApJ4ZesrSCSBpkBenPkiQeYgHlv5GFtLtgIwPnI8f5n8F6bGTuWz8z8jtyaXYHMwqUGp+Hn59dLVKXoCBw4abY1u5Z7KDmNz2Pj+wPf8be3faLI34aXz4pEJj/D5hZ+TVZmFr5cvy3KX8eHuD13aNdmbnJ+DzEE8NP4hLk29lKqmKuL941Vgeh+iwWrHS+8eE9KgdkIUin6JQzpc5mAAgzAQ7x/PNfOuoayxDIHg1vRbuX7w9QwOHkxhXSHh3uGkBKY43bgPY7VbOTPhTKbETMEhHZgNZqSUOBxqoULhjjJC+hFN1iYqmysJNYcikTQ5mrQtTlsTOOzg1Rq4mxyYTHJgsvN4QMAATo87naW5S5kYNdElX0hlUyV/XfNXbk2/1WmAAKw7tI4VeSu4dvC1DAweSKxvLCaDyZlYTnHy4qX34oYhN7CzbCfjIsdhc9jYcGgDM+NnUtdch9VhJdAc6NJmT/kenlr7FBHeEaQGpbK/cj9P//I075z9DhOjJ2LSmahoqnAxQnRCx9SYqS79BJoCT1h+UtG9NDR7CEzX62hQeUIUil6hrrnO9bnscEBzHXj5gO7Izi7N9mbsDjsWo4Ubh97I3pV7GRc5jmZ7MwFeAby9422nG7ZE8ub2N5kUNYnxUeOPGiBvkzae2/icS9lZCWdxccrFzkUss0HlfVJoqLfJfsLGQxv5KvMrcqpzuHbwtSzJXkJ2dTaXJp3HrJpqInZ8DZPugZRZ4N3qo5lXk8e8A/NYkL2AoSFD+ee0f5JXk+fW/77KfVQ0VriVry1cy5kJZ/Lt/m+Zd2AeQ4KHcP2Q6xkcMtitruLkYnBAKg+Pf5i5++Zi0pv45/R/0mRt4tc//Zoaaw2Xpl7K9NjpThnf4vpibh52MwW1BWwv3U56aDrnJ59Pbk0uT6x+gpTAFK4ZdA3PTH2GT/d8iq+XL1cNvIpBQUplrb/QPls6gJdBryR6FYoeprC2kAXZC/hu/3cMCh7EDYNvYAhG2PAO7P8BUs+C0TdBaKpLO6vDysZDG3lr+1tUN1dz49AbGRIyhIfGPsTcjLlY9BauSLuC25bc5nbOQ/WHjjmu/Np8t7JNxZvYXLSZF7a8gEEYuCX9FsZFjMNitHjoQXEqoYyQfsDe8r08uvJRCuoKuHvE3fx59Z9psDUA8I/N/6Y0+WLus9aj//J2uOQ1GHE1oClX/HvTv1mUrSUp3F+5n1X5q/jbaX9zO0daUBrBZne/+0lRk3h96+t8tu8zADIrM1mev5yPzv2IBP8T0ylX9A/WlWzgiTVPOI83FW/igTEPsK5oHQBP/fIUDung2sHXAhDlE8XLW152qqkdqDpAckAyD49/mIzKDDIqM1iRv4KbhtyE2WCmtrmW3/z0G94++23GRIzp8etTHD+NR3DHKq+z9tKIFIpTD6vdyhvb3mBuhpYcNrMykxV5K/howPUkrn1Zq1SyF7JWwvWfg09rdvUdJTtcBEce/vlh/jjhjzy38TnqbVoOp4/3fkx6aDrbS7e7nDfIdGxBmjjfOLeycRHjeG37a05Pi40/buT1Wa8zKXrS8V+84qSizxghQohsoAawAzYp5Snvj9Fsb2ZfxT4OVh905l5w4HAaIIf5IHs+k8/5K+EF20jc8A4MOh9MvuTX5JNRkcF9o+5z+uhvLdlKs6OZ6wZfx6d7PsUu7YRaQrk09VISAxIZHzGOdUXrAZgWM5WR4SN5Zv0zLueraqriQOUBZYT0MXKrc8mozEAndKQGpRLj656gsi1VjVXsLNtJQW0B4d7hDAkZQqi39rCqa6zm84wv3drsq9hHrG+sU/Fq7r65zEqYRZh3GE32Jjc55wNVB1zK6qx1OHA489gArMxfqYyQfsKR8oSomBCFoucoqC3gy0zX+bm6uZr9spHEtoWFm6FkDxTZoKECwgaxqmCVi+AIaPP4w+MfpqCuAIGguqmasxPO5l8b/0VRfRF6oee6wdcdVaL9MEIIzk48m4XZCwFI8k9iRNgIdpS5yrF/f+B7ZYQouscIEUJMBhLb9i+lfL8DTU+XUqqEAICUkoVZC3ls1WMuOxcC4VbXbDCztGw73+R+yxsTfs3QFiUrL70X5yWfx0ubX3JOOrMTZ2MQBtYfWs/tw29HSkmttZY3t7/JRzNe5HmrD9lpc9BJSCjNpsJuxSAMNEtXZQujXmVL70vsLd/LHUvuoLyxHIAY3xj+e8Z/XeKC2tJka+LzjM/596Z/O8vmDJ3D7em342/yxyAMeBvckwNaDBaXIEazwexUvzIKvVt90AyPtrS/h30MSrqxv9BgtWPUu/79THqdUsdSKHoQvU6Pl97LbUFSeFIRLM2A7+/XPnuH4D3rd25VfIw+LM9dzo+5PwIQ5xfHyPCRnJ98PgadAZ3QUVxX3KF40OrmakoaSrh7xN04pIOi+iK+zvyaOH/XHRI/oxK3UXSDRK8Q4gPgWWAKMK7l55Tf1TgerHYrGRUZbCnZgrfBm4qmCkaFaVmsG2wNRPpEutS/cuCVLMpehL/Jn50GwaHmKkB72Xt3h6vM6qLsRRh0Bhptjby69VVe2/YaH+3+iFuG3UL07oX4b3yf4YueZNjiJ/Hb9D4x2b9w+/DbXc6XGphKaqCrn6mid/ky40unAQKaX+7yvOVHrL+3fC8vb3nZpey9ne+xt3wvACaTN9cMvAqdaJ0izHoz8X7xlDSUOMvmDJnjDFBPlEbOjXYNMp8WM80leVWcX5yLUWIxWDgt5rTjuFJFb9JodWBs545lVHlCFIoexaQ3cUXaFS5l8X7xBPnHulYcejHs/rb1uL6MyQ7XBSaB4KKUi1yeF7k1ueTV5rG1ZCs2h42C2gLmZ8+n0X5kdcTDjA4fTUZFBv/d+l9e3fYqX2V+xc3pN7M6f7WzjlFn5Nzkc4/vohUnJd2xEzIWGCI7sm/nigQWCyEk8JqU8vW2Xwoh7gDuAIiPj++SgfZFcmtyeWv7W3yz/xsivCP41Yhf8eW+L7l52M2cEX8GWdVZ/HHCH8mpzuFA1QFifGNYd2gdYyPHEmQK4rlNz/PClhe5b9R9DA0eSo21xu0cjfZGXj7jZdYWriW7OptJUZMYFTYSfrnGra7+wDKuPusvDNR5s6ZsO6k+MUyInkyEh4REpyJ94b602W3sLNvpVt42H0d7KpsqsTpc/fglkrKm1qSUQ4KH8PSUp1l3aB1eei8mRU3Cx+jD9YOvp85ax7jIcQwLaU1m5dNYwY1JF5AWMZp9lRmkBA5gYsBAKpoqiNV7k+gdyfiYKVTq9Rh1RnyMPkyJmaJEDrqJ7rg365ttHmNClBGi6Ch9Yc7s79Q015Bdnc19o+4jqyqLMEuYtlthb4BLX4e8DRA7HsyB8PHlLm3DK3J5eqo2rzdYGzgt5jS+P/A9NumqcJdTnUNKYArv7XyPSN9I7hl5j1sdT6QEpfDO2e+wOn81ZY1lTI2ZyrDQYcScFcPPeT+jF3qmxk5laMiRFbYUpw7dYYTsACKBwuNsd5qUskAIEQ4sEULskVKuOPxli1HyOsDYsWOP18DpF1gdVt7Z8Q5fZHwBaKvZz298nntH3cvjqx8nzBzGB+d+QIyf5uu/tmAtdyy5gwBTANcMvIZXtr3i7Otva//GW7PeJCUwhczKTGe5QWcg2MufxIBEEgMSXQcw/CrIWeVaNvgCAhf+kdMzF3O6fyzUl4HDCrcvg4gh3fFr6Ff0hfvSoDdwfvL5LvLKAKfHnX7ENnHeEYR7h1Nc35qo0sfoQ4J3tPN4RcFKnlz7JOHe4dgcNj7Z8wn3jbqPxTmLsegtfJX5FQ+OeZA5w+YAUOQbym9+/BOVjZXE+cfxY86PfOTlyyfD7mPaloXQUA7Wv8HtSxk95v4u/R0o3OmOe7Ox2Y6Xh4zpKiZE0VH6wpzZ3wk3+FDfVMXLW14myieKisYKGu2NfDrzFRhwvvYsB8jfBEJAmzXhDUkTeHDpbwizhGExWFiWt4wr065kae5Sl3MMDBrIsxuexS7t5NXk8dzG53ht1msdGl9aUBppQa4JjUeEjWBE2IjOXbjipKPLjBAhxHdouxl+wC4hxDrA6TwupbzwaO2llAUt/xYLIb4CxgMrjtbmZKO0vpRvMr9xKZNImu3NRPpE8pfJfyHaNxrKsyFvHYN1Bp6f/i/2V2fRZGvi/tH387+9/3MGsX+V+TX3j76f/279L7vKdhHhHcH1Q66ntk2GdBdSz4JJ98G6V0HoYPyvQGeAyKEQMRRWvwD2ltiQskxlhPQhTo87nZzqHD7d8yk6oePW9FsZFznuiPWTGuv4+7hH+fuWFzhQdYBYv1geGfUbBjdoPsaNtkY+z/gcwGmomPVmQs2hXJZ6GfW2eoJMQfyc9zOXpl6Kv8mffGsNI8JGkBaURnljOWcnns3+qv3k1uQSVZmjnTggDqoL4OBaMJghbjyEq52Q/kK91U6oj+tjw0uvo0nFhCgU3YfdBoVbIG89ePniG5rKo+FTecphZ2PZDkLMITw9+BZSKgqgrUdWxDC44j2Y9wDUlcLY29hStou7RtyF1WHF5rARaApEILgi7Qq+zPgSo87Ibem3se7QOuyydXHBIR0ui1YKRVfQlTshz55oQyGED6CTUta0fD4LeLLLRtZPMBvMRPhEkFuT61KeEpjCx+d+TJh3GFTmwqfXQPEuSs76M3/Z8TUVTVp+D4Mw8MDYB3h2w7M4pAM/kx9PrnmS6bHTuWHwDWwq3sTrW1/nhcl/9TwA/yg4888w9mbtRXH+g7D6Py3fxcDk++Dnf7UMNqC7fg2KEyDCJ4IHxj7A1QOvRid0RPtGo9d5DhQHwGhmwge38uoZj1A8JIqQ2jJi594N12mGh0FnINE/0SWe45Zht/Cfzf9xxp7ohZ7HJ/7JmTHXz8sPg87AS1tecraZlTCLAJ8W1z0hYNLd8Nn14GjZ1rcEwZz5yqDtJ3jOE6J2QhSKbiVnFXx4iZaUGMAnjNSJd/NSraA4+Tp86sqJWPI0nP9v13YGLxhyEcSMheZa8ItmTNE6nljzBJVNlVoVYeDxSY9zRdoV3DjkRvQ6PT4GH+Z+P9dtGAFe6rmv6Fq6LDBdSrlcSrkcOPfw57Zlx2geAawUQmwF1gHzpJQLu2ps/YUgcxAPj3vYJRg4PTSdkWEjNQME4NB2KN4FJn/W0uQ0QEDLVPrTwZ8YFzGOYHMwIeYQihuKmZsxl9yaXObum8vksFGkhBwlOZzdCk01ULhVe0E8THU+6PTaT9rZYPKHKvekRIrew6gzkhCQQJx/3NENEIDgVJh0D1HzHmLExzcQ++39kH4FhGpb6AadgeuHXI/FoCWT8jZ402hvdAl+t0s73x/4DlldBAVbaLbWMz9rvstpluQsocnLB6b9Hs56GvI3txogoMlG7v8RSvZp93aTewyTou/Q0Ow5T0iTTe2EKBQnhMMBpZlQsBXq3RMG01wPy55pNUAA6kpA74WvTxjJVisRegskzYCo4VCVp82zbZ/PATEQNhDMfhyoOuA0QEB7b5ifNR/hcJAYkEicXxzBlmAenfCoi5Lh6PDRDApWiWUVXUt3xITMAv7QruwcD2VOpJQHAOUsCEyKmcRH537E/sr9+Hn5MSRkiKsaVnOLspCXN2X2Orf2FU0V3DbsNg5UHeDN7W86y30N3vx3wp8Z4h1N4JGCyisPwo9Pwva52qr14Itg9I2wqUVd2egNl74F2SvgjRngEwaXvQnJM7rm4hU9h8EIE+6E+IlQmaPtdEWNAJOvs0p6aDofnfsR+yr24W3wZkfxFrduShvKad77HeaFj9J83tMeT9VcUwAr/k+7f067H6JHQcHm1grlWfDRZdr9lzobzvkHBCd18QUruoJGq8N9J0SvAtMVihOiqQY2fwg/PAG2Rm0OvuRVCG+zM2xvhtp2mcp1BghKgI3vQlkGePnA7Kc1w+PzOZrrlW84XPqG2/O5tL6E9pQ2lNJsbwBadzqmxkzlo3M/4kDVAQJMAQwOHkyET0RXXblCAXThTogQ4i4hxHZgoBBiW5ufLGBbV53nZMeoMzIsdBgXpVzEzPiZbnK8hA8GvRfUHGKyxT0Z3bWxsygo3cUb299wyunphZ5R9TVM/fRWQt45T8uk6om9CzQDBLRAtl1fa4aGl48WIxIzBr67Dza8rdWpK4H/3ajFqCj6H2Z/SJoKo66HAaeDt7vGfGpQKucln8fp8aczKSTd7ftrk87Df+9iAOKK9pLo66p2E+MTTXzpAe3AWg/L/q4l02xLYLxmgABkLIItn3T+2hTdgid3LJPaCVEoTozCbbDwYc0AAc0D4YcnoblN/g8vXy3QXOggcjgEJ8PgC7SFnbIMrU5zHXz3a8jfoBkgALXF8L+boCLb5ZQTI8e7DePiARcS7Ov6rmHUG0kPS+eilIuYETdDGSCKbqErd0I+BhYATwMPtymvkVKWe26iOG4ihsINX8OPfyV910L+M+FxXtr7CTXWGuakXM4ZdfVYTUHIoTfz2YHvibCE8ZvYsxi84kWtvXRARZY2oe36GspzYNgl2mr07m/cz1e4FQaeDyOu0oyf9u4yjVVQnQfBid184YreJr3yEC9O/Asv7v6AKmsNNyVfzCy7EXxCAAjd9CHPX/0eb+T/xNrijYwLHckd8WcR/ukc146MFgiI1Yzb8XdoK4Ft2f21Fn9kVsms+hqejBC9TiClxGp3zyGiUCiOQkWWe1nmYijaoc2LtgYYcwvoTXD+f2DfAk12d+gl8M3d7m2ba12PGyu13ZGgRGfR2PDRPH3aU7yx4y3qbfVcmXYFM9vld1IoeoouM0KklFVAlRDinvbfCfH/7J13eBzV1Yff2b7SatV7lyXZcu8NMGBM7y2B0ENCb6GXhJ6EEJKPHkogCYTee3PANmAb496brC5ZvW7Rtvn+uNJK65UtyVZb+77Ps4+0d+7cuSPNzs6555zfUfSqqrp72E3SXxQFsg6DC9/B5HIw3xLP9Jzj8ZT9TMz7VwrvBHBldCbnnP4Mpm2fE/7pHSLXoxNTFLx6pnDxHnMfvHMJhMdB7rFQuizweFlHwPTfgMkCNVtAqw8cS2sQ3hLJQY9R9XHUh7cw9fCb8JgiiPnpRRE21dKhxp1/ArlLn+Mhj52WlKlEFG/CWLRZeD42vd81kNcF2fNEjHNbbWBoFkDGXGGoSEYcTo8vKCdEURSMOi1Ot1caIRJJf7D04F1ImgjLnoHNH4j3zeUw9jQRhdDJpvfFd/dXdwXuq9vjvqkziu/2bkSExXBK7mnMTJyG2+smNSrrwM9DItlPBiMnZDWQDjQCChAFVCmKUgP8VlXVVYNwzGGl2lZNUXMRBq2BnMgcfwXpXrHVQ9028VAfly/UqUCENzXsAmOEeDWXgyUe4kaD3iT6dG5rKsPaVApLn/EbIAA0lhC7+WMYfZJIetshQmY44hZwtggDxBgB9jrhCm4uh4gkiM7uWp1JGAsFpwgDBCA2F058DD67SYRrKRo46W8QM+oA/4KSAaF1N9RtB0UrrifLvo1Dj89DcUsx1bZq4sxx5ETmoNfq976D0Qpx+Vi/uVe8tyTA/D9A9QbIPQbi8uD9KzAAceXdPuZ5x0JnLcWpl4IhUkj1Koq4dtJnQdlPYntEivCOVK0Tq3jRWRArr6+RgtPtxagLNjSMOg1Ot48I0zBMSiIJVZInw8TzYP2b4r0xAubeAB9c0dXHHA2rXw3cz+MEt00sAHZ+70+/XCSfH3WnEP/Q6CE2D7s1hV11G2lubyYtIo1MayYACRHB4dwSyVAzGEbIl8AHqqp+BaAoynHACcDbwLPArEE45rCxo3EH1/3vOn9tjrkpc7lvzn2inse+aCqFD68VSd4gHv7Pf0PEdr52jlANAhh7Bqhe2PopHPswzLi8a5W4ejN8fhvgE4lqe+JsFvrgaTPgoo+gvUWssPj7BhYxYsmjMO0y8YCYNAESxoG1W5yoVg+TzofUKWL125oC8WNAOxiXkaRf1G6Hty+C2o4q6WkzReXcvSR4q6rKwpKF3PXDXXh8HjSKht/P+j1n5J6xd0NE9Yokx1FHi9/TZsG2z7pyhI7di6p26jT41dtgjgK9RUhMd9YNyT4KTntaGMVeF0Rlw6qXxHUK4kv5V29D5tz9+KNIBpqewrEAjHqZnC6R9BtLvBDimH6ZWByMzREGR/doA0Uj7rd7ogJzrgNXq4hICEsQBsmSvwovs0ZHy3mv8cL65/nP5v8AoiDtM8c8w7TEaUNzfhJJLwyG73x6pwECoKrq18A8VVWXA8ZBON6w4fF5eH3L634DBGBp5VJWVffB2bNrcZcBAqKadOly0e62d7Vv/lAoZqgqfH1P10MmCO3wkh/EKnLusYHjKxphSDTsEgWOFAWWPwtly8UqSXicMEosCaAPh/zjhcGz/StxvLSZgQZIJ3qj2D76BCEHqDP06W8lGWTWvxV4bZSvgJ3fCqPW0RTUvbS1lHuX3ounQy7Xp/r4409/pKilCOwNgYmRnbjssPgRWPRnWPyo+MLrNEAAwmJF8cHupEwRK3lpM0ThrFX/6jJAAIoWiWTK7HmQuwBaK7sMEBA5SJ/8TsxJMuy0e4LVsQB/OJZEIukn5ihImgRp00W0Qeo0oSQ45hSR+1H2kygc3B2tQSzQLLwPljwG3/0J2irhi9u7pHx9HrY27fQbIAA2t40Hlj1Ak7NpyE5PItkXg7GE3aAoyh1Ah3+RXwKNiqJogYNKQsXusbOyemVQ+9aGrZw66tR971yxuuv3/ONFHOjyZ0AXBkffAxvfEyEp0KWcASLkppOajhgXn1f0P/YhKFoiEn7TZ8DPL4nwq9bd8NG1EJ8Px/8Rfvg/mH2tUNZoroQznoUfnwDnDpjxG6GS9fXvRW2H3GPBGL6ffyHJkOB1i4f57sTmCgPxlTNEyN3sq4WRaRHyzI3ORhyeQEPDq3qpr1oLXz8swqSOukNI+HbSsCvwGA2Fge8biyB9NqRMhd3rhdFhCIf6nfDOpSJca8wpwlix13ftV7kWJv9K/N5SSRB1W4VnsAf1LsnQsncjRBYslEj6jaqKPMxFj4jFmamXihDUEx+Fn54T3uHDbxaREqc9BRvfF0bLlAvFd3p3fL5ADwpQq7qCDlnUXESzq7nvYeMSySAyGJ6QXwFpwIfAR0BGR5sW+MUgHG/YiNBHcHT60UHtk+L7UPIk63Dx0xAuVouX/BXqdsDudfDNvTD+nK6+nclmGq0IleokZXrX71VrxapI1hGQNQ++ukeE4lSshrWvQXMZ7PyfWDWZcjH87wGo3iQS3t69FCpXi4fMhfeBIUwUJ3znEihd2u+/i2SI0ephzB5G79SLhWRj+Qrxf/38NtjcpX4Wb47HarAG7GLQGEisLxJfhru+hVdOg90buzqk7uHC3zN53OsRuvUbRdV1Nn8IPz0vPCFNJbBzoUiknHlF4H7dDZ1uKi5+0mZI8YMRgNvrAxV0muCvDYNOg8MljRCJpF/s3gCvnA5Fi4WU7v/uF57hHx8XCll12+HLO8SCz5d3iTyQ2m1CJKZ7MWEAVOFB6UaqJjhJa2LcRGKMckFHMjIYcCNEVdU6VVWvV1V1iqqqk1VVvU5V1VpVVV2qqu4c6OMNJ4qicFbeWf74SgWF80afx9SEqb3vnDkXpl0qfm7/Knh7zSaRkDv7anGDMoTDmc+LxLNOMmbD5AtFqBVA6nQR1pJ9OJzwF+HFyJgN03/dtY+jUcijHvsAnPhXEarVPS8EYMvHMGq++H3dm0hCgHFniEJ/IBLIHU1Cjrk7y57xhzWlRqTy2JGPEWWMAsCit/Do+CvJWvlKV39PO9Rs7nqfPhNmXdV1vdUVwrn/gaM7vGbWFDjjH8IzV7IUPC446i5hXHfidgjFFhDjTPs1ZB7WtT1xvLh2tR1hftFZcPLfRE0TybDidHsx6nv+yjDoNDhlrRCJpH/UbBbeju6s+S8cebtIMD/yDvH7lo9FuFbZCrHPokfguIe7FiV1JrAkw5kvCPVLAHM0o+MncNfMuzBoxP00zZLGPbPvIcIo5c8lI4MBD8dSFCUfuBXI6j6+qqrzB/pYI4GsyCyePPpJylrL0Gv0ZFozMer6kPpiTYYTHoGmMpHrsSdRWXDEbWK1uaVShKLE5HQ9AALE5cIJfxauWa+rS2Fr12L45vddrtmkiSLM6ueOCuq2WhHXf/yfxQPrnpgiu/TGe5IQlIw8orPg7JeE10OjFR6QPQmLEV6TDuakzOGtU96izlFHtNZE+psXCZW07nT3dlgSYMEDwsviaRdFtL66S3g4QFybCx4U1xqq6LP0CZjx28AxY/PgikWgMYhEzO7HMIbDzN8KI7i9BSIzICLhQP4ykgHC6fb1qIwFnepY0hMikfQLXQ9ycof/Dr65D1o7pM9NkeK7euU/u/q42qB2B5z3uohyMEVByjQwmESuZlsNWBIxR2fwS5+XOclzaHO3kRyeTFxYXPAxJZJhYjByQt4BngP+CRwS30pWo5VxxnH931FvFnkah90Ihf/rSigbdQzkHQdGi5Bb1eqF3F53A6S1WiQdRyRD5pyudkczfHV3YGzo7vVCahdEvH5nYvA3f4DLvhAPp52Jv4oC48+GhfeL+U3oFhYmGdmYIiClIxRQqwvMvVAUOOpukczYjRRLSpeS29wb4cOruzbGjBISko3F4jqMShcS0Ykd1/rmj7oMEBAetaVPipW71mphPOccLVbvOokfI4QNorqFFe6JRis+F5IRxd6UsQD0WhmOJZH0m+TJYpEwfaYwJKo3CWGaTgMEhMpl8Q/g7pYbao6GtKkiWsIQLu7rhg6DJjpTvDrQarRkR/WskiiRDDeDYYR4VFX9xyCMe/CSMQd+/RUU/yge0ta+Dv85Fc55WcjmVqwSXpDj/yQMlB1fwWe3gK0GRp8MC+4XSb8gDJPu6kOdaA0w73ZRe2HFC6LN5wEUuPRzobTlaBYPsc0VYkU76zDxwCgJPeLHwKWfdf1fM+cG53TsScFpYE0VKm3WFGGw/vQCrHhOXD9H3SnC/8I6YpF7UN3CVgseN3z/mKgzc/yfQaMRamtR6cJg3pcBIhmx7MsIMWilJ0Qi6TcRyTD3erFwaK+DmVeKRZ89qdsGpz4F2z8XBkfmXDBFw1sXQ+FCcd8+5f+EwqBGO+SnIZHsL4NhhHyiKMo1wAdAe2ejqqpSY3NvaLQi+TZpEnxyI2z5SGiHL7xXxNNbEkWYzLuXwYUfiITxTq/J1k9F3Y8znxer1JYEUfzo5xcDj5EyFd77jTBcOolMFw+EEUmQUDB05ysZGhIK+vd/NVog50jxAmGALHtS/O51CcW0mBwYc7Joi8kS116HzC8ghBE6i2fVbIb3fg0XfwJH33nApyMZXkQ4Vs8POAapjiWR9J/d6+H9buGqK/8FJz8mJNeNVvFs4GiEglMhfbp4gZAuf/PCLlXElgpRf+mKxUKaXyIJEQbDCLmk4+dt3dpUIGcQjnVw0VYNG98Rv5ujRez8+HNEYcOIJHEzqt8pktVqtsCmD0TfLR+JWP2YLBGGM+da4RFZ/6aoB3L8I8Lde95/4dObhepG2gw46a9iXIlkT9wOWPvfwDaDRXz5LX9O5GskTRBJ40seE3HJOUdB9pFCwaUTez007oKk/QhXlIwoHG4vBu3ePSHSCJFIumFvELl5ZSsgbnSHFzgjsE/dtsD3Mdliv7NfEoqVXo8oDtwZfm3okMtvqQqWZfd5xfOBNEIkIcSAGyGqqsrgw/3FEC4S0ut3gDFSxPR/98eu7WkzIP9E+Pg6mHQepE4VEryRGYG1PGKy4dTHRWy+3txlaKTPgks+7ai5EAvmyKE8O0kooTWIkK7OWjUgcpe+uEOE9IHIMznujyKJ3BIPZT+LgpjjzujaR1HALOUgDwb2mROi02Bvl0aIRAII42HFi7DoT11t6bPhl6/6azUBwbWPbLVCvfLj67uKFmt0cNrToO0meGO0iAVGW13g/kGyvRLJyGbAJXoVRQlTFOX3iqK80PE+T1GUU/qwn1ZRlDWKonw60HMKCVqqRE2Go+4QN53GIlHfozvlP4OrVXg6tn8t4j8z5sIpjwtvSUsVVK6BqvXgcwtjZE9PR1i0UCSSBsjBh7Ol4/+/TqineJywe5PIKdpbxfGmUihd0VWIsK1GGBO124Q4gqnjOjFGiJW47pV2VRU2fShCAZY8BsVLhCTvhne7+ky7LEi7XhKaOPZhhMhihRJJNxqLRV5cd8qWQ/XmwLbkKSKEtRN9uLh/dxogIMJdt34WKKVvTYGT/x4oVlNwupA4l0hCiMEIx/oXsAqY2/G+HKGY1ZtxcSOwBTj0CgJUrhUrzGXLhbv25L+Lh7/usfad1GyGdW/AvFshvgBaa+C1s2DO9cIrUvKD6DfhFyJhPTJ1KM9EMlw0FImChDu/Ee/HnyPCoz65Xnx5JU+Bs/aoM7PzW5Gz4WgU19u5/4FPfycMYK0eDrtJ1ACx14kClj0lorc3w3EPCc9cWJwwnOdcBx6HkJ8sWgIee/B+kpDDua9wLFmsUCLpwusKrv8BIsy1O4ZwUS8se57oH53Tc4Fge71YWKRLYp38E+E334kQrLBYEYYVLuV3JaHFYFRMH6Wq6qOAG0BVVQeg7GsHRVHSgJMRsr4HL769fEmvf1sYICBWpj+5Qaxkdy/iBsKN63aKVe3v/yYS0Vf/WySuexxdBgjAhrdh16LBOAvJSGTTh10GCIiq5Y1FXV6IqjWw/B9d0s2NJV0GCIiilov+JPYB0W/JX4WRses72PSRWGVT9vgoT/qVCBOccK7YXrMZvn1IeEa+fRhadkNs7qCeumRoaHf70Ot6vpUbdRrs7h4WTSSSQxFTlJAn705YTFcolq+jsGfVWnjvchF2veSv8NHVIsx6T8afLRaCOvcD0BlEvsjEcyG3IyRWIgkxBsMT4lIUxYxIRkdRlFF0U8naC48DtwMHZxnP2m2w/h0o+R7GngljTupKULM3BCeYARR+B5N/JTTEt38hVI4yD+vKEbHXQ32h+D1hnAi52ZNdi2DKBYNxRpKRhNcN23pwNFZvEkUMqzeJ9zu+Asc94suqdXeXAQKQOCE4fACEQovBIrwaOiOc8ChseEuEfhWcJjwwzhYR5meJF7LSK14U9UNyjhIV1mXBy4MCh9uLQbO3xHQtdukJkUgEjnpImSLUJ4uWCA909pEinPq7P4vv/ILTeg5VXf2qyAH5+Z/COzL2dHEPL18D3z0I4Qkw43JInS7kzyWSEGYwjJD7gC+BdEVRXgMOAy7dW+eOfJEaVVVXKYpy1D76XQFcAZCRkbG3biOPlkp443xo6DAYSpeL3I7TnhIrG0aruJl0Pih2klAAmz+ElmqhlPH5bUIitROjVTxggnDH5hwpwrG6kzF7sM5K0sGIuC61esg+GspXBrbH5UPpsq73GXPB1BHtaIoUoQCuDiWr+p3Ck1G9MXCM9hYo/Fb8vv1LOPYhkfwYmS6+JAtOFUmSncSPgRP+IvYzWoVam2RYGOhr0+n2ot9nxXRfj9skku6MiHvmYBMWK9QF9eGQNl3kiNTtgFWvQN1W0ad0OZz5QvC+ikYs4liTRZHipU/BpPPh67u7QrU2vSdqi/VW+0kiGeEMuBmtquo3wFkIw+MNYLqqqov2scthwGmKohQDbwLzFUX5756dVFV9QVXV6aqqTo+PDyG3Y+22LgOkk85QGRAPaVMuEtWpO8mcK+R6d3wD1euhrVasKncWIdIZ4YhbxA0u73hRnNCa0lWwsHOMUccM6qlJRtB1OemXojhgJ+mzISpTVNsFsKbB4b8TSY9bP4f2NiH1rDWI7du/FHlG3dVVJv9KGMydqD6h3Fa7TchDG60w+2phBHVHqxOhB9IAGVYG+tp0un3o95kTIsOxJL0zYu6Zg4k1Bc74h/ge3/CuiFRInwnGMJj/e3GvPfoeEaI9/uyu/cJiRPHCtmrY9gVs+VgYI6PmB+aKeN2iirpEEuIM2FOCoih7BjJWdfzMUBQlQ1XV1XvuA6Cq6l3AXR1jHAXcqqrqhQM1r2Fnzxh6f1u3dkMYjDlF5HgoGvGA2H03j1OEZM27XSSnKRpRjDD3GFGksG4beFww/lxorRLGSly+TFI7lIjLg4s+hLrtXf9/jQ6SJ4pkyKgMWPmSWFUDYXyc+KiQcfY4xYrbj0/C+W8JZRaDReQVrX098Dj6MDj3FVEvJC5XfNlKDgnsLs9eE9ONMjFdIglk1DFw5RKR5xkeL7zO6bNErhyI+/QJfxGyvEffLYRo3E745g9w/tvQsFMYKXH58NG1weMrcpFHEvoM5FX8t31sU4H5A3is0CF+jMjZqOkWbjXlYlF5GkSi2c8viRWP/OPB0y5WQGb8RjwIavUinlQXBov+3DXGhF+KMQzhgWFXcTIJ+JAlIlG8upM+U/wsWQrLnhGyzlEZIhRg0Z9FONXPHXoQ6XMgdlSX8dpSASu6hQto9ZB3rEiGlBxy7KtOiKyYLpHsgaKIkGlDBJgiRMj1T891bfd5RW5n9UaRN9LJSY9BYoF4dXL47+Dti7re682QvYdwjUQSggyYEaKq6tG99wJFUY7tCNnqaYxFwKKBmtOIICIJfvkKbPtSPPiNPgFy5guvBwhVK60OJl8AG94R7UfcDC67WB3JPhISx8LZ/4QdX0LxUlG/IXd+V/VUiaQ3HM1w/J9g0/uw+SMYdTREZ4vkydZqyD5CXFfdvWc58+G812Hje8IDMu5MyJo3fOcgGVbsLi+RZn2P20x6rcwJkUi6U7cTlj0NWz6CpMkw9zoRwtoZIguw9En41TtCRKZuB0w4GzIPDx5r1DFw4XtCSTM8AcafBcmTh+hEJJLBYzj8eX8BejRCDlpic8UNaO51wdsM4aLi+df3dLX970E499/ioc8/Rg7EXgOzrxn06UoOQsJi4P3LuxLRN7wrvthmXAFjTu55H7NVbNvbdskhhdPtJT7C2OM26QmRSLrhbIXPbxXy5gC7voWKlUItcMmjXf2MEaKocFYvXg1juPBi5y4YvDlLJMPAcBgh+6wZcsjhdggPyJ7sWiJWTeLyhcyfRHIgtFV3GSCdFP4PnI0QkbD/47ZUiRok9gZhbCdPEqECkoMOxz6KFQp1LGmESCQANJd2GSCdtLeIcNewGHG/jEwTypc95dXV7YCq9SJPJGmCiIaQSA5ChsMIUYfhmCMXRQfWVFG0qDtaHbz/G4jMhF/+F6LShmV6koMEg6XnNl3PK9t9orUaPrxGrPJ1ctaLMPEX+z+mZMTicHsx6veeE+J0e1FVFaUnMQ6J5FBCZxIvjzOwPSIFrlgijJCIRBGuvSfVm+GVU8FWJ94bwuGST6Qcr+SgRFa6GWicrVC7FZrK+tZfp4fDbuiSSgUhk2pJFApEsTlC/ap19+DMVxI62BugZot4+O8vSeODY42PuVfI+HbH2SokePty/VZvDDRAAL68A5rL+z8/yYjH6fbt1ROi02jQKArtHpkXIpEQnQ1H/z6wbdQCUf8rKh1SJvVsgIAQpuk0QEB4sFf8M7BaukRykDAcnpDiYTjm0FC7TRQVLFosDIkTH+2oimra937ps+Dyb6BsBdhqhLTq8mfg2Adh9Svw37MgIhlOfwZyjpZVUg9FKlbBh9dB7Wbhxj/9GSFa0NdVZ0sCnPU8lK8SRkLSeEidGrj/ntfvCX8R1Xr3dv22twS32RtEiKHkoMPh8mLQafe63aTX4nB5Men33kciOSTQaCBjFpzwCDSXQVickEs3Rfa+b8Ou4Lb67SI0S2MI3iaRhDADWSfkrH1tV1X1/Y6f++wXsrgc8M394gEOwNEI7/8WLs+G9Bn73ldRIGUyJI6DL+8UkqlTLoIVL3bdkFqr4M3zhSs3YcxgnolkpNG6G96+RHyZgTAi3jgPrvw+sEBlb0SmiVdPuB1CEKH79fvBFSJpslPmd0/i8oVsr9fd1ZZ/kggvlBx0tHv2LtELYNKL5PTovfaQSA4Rmsrg4+vEwo7e3FGLSQeXfBooqd8TBaeIauvdmXop6KQBIjn4GMgl9VP38TplAI8zMmmrhh1fBLfX7+z7GFo9zLkepv9GJKvtuSLiae+qtC45dGgu7zJAOnE7oLF44I7RVgPbPgtu39f1mzAWLngf4seKcMKJv4TjHhLFNyUHHQ63F+M+jRAtdlmwUCKBphJhgIC4V6uqWKzpy/NAxlw49QlR4NAUCQsegPwTBne+EskwMZB1Qi4bqLFCElOEiAPd03AIj+/fODFZcOIjULMVlj8r8kICxpNV0A85zFFiNW3PMKew2IE7hsECMaOCvyT3df0qCuTMg8s+F3HLlvgDS3SXjGicbt8+PSGyarpE0oEpSrycTYHt4X1QIjRHwrRLheGh+npWz5JIDhIGJSdEUZSTgXGAP5hcVdUHB+NYI4K2WuGhOP4RKFok1Cw0Wmhvg+QJ/R9Pqxf7nfQYfHiVWEUBmHs9xBfse1/JwUd0Dpz4V+He72TebRA/et/7udqE1KPbKQwMczTU7wBHA0SmQ3S3pPTwWDj5b/DaOV3hVWNOgaSJvc8vLFq8JAc1zl48IUadFrvLM4QzkkhGKEnjRU5o9UYRRqVowOPu2/20k70lrkskBxEDboQoivIcEAYcDfwTOAdYMdDHGTHUboN3fw21W8SD4qb3RQy/ooEjbgXtAdRMGHumeNBsLBFqWYnjwNiD1Krk4EajgQnnQuJ44eaPSBLXgiF87/u0VsN3DwthA4DYPBEq9daFIsHRHC2qoWfO7dona57IOarfIVbxEsdJz5sEAFVVad+HOhaAUa/BLmuFSCQCc7S4/zqbxMLiMff3LlIjkRxiDIbM0lxVVS8GGlVVfQCYAxyc1fZ8Plj5sljtyD8R1rzaJaWr+kRl1N3r9398vRFSpsC4MyBzDpisAzJtSQiiN0Fqx7WQMVtU2t0XFSu7DBAQhsXa14QhAyLx/MOrhRevE41GFMUaezrkHCkNEIkft1cFBXT7MkJkOJZEIqjbCZ/e2BWO5XXD1/dA1bphnZZEMtIYDCOkM3DdrihKCuAGsgfhOMOPqxV2fiN+TxgDlWuC++yZUCyRDAW7Nwa3VawKrLzbWAy22uB+EskeONxeTPsIxYLOcCxphEgktFZBS2Vwu3wekEgCGAwj5FNFUaKAvwKrEXVB3hyE4ww/BosoQARQux2SJwf32ZskqkQymCSOC25LmSqKHXYSnSW9HZI+4XR7MfZS/0N4QmROiERCRLJ47UnkwRkUIpHsL4NhhDyqqmqTqqrvAZnAGODhQTjO8KPRwozLIWEcbPscJp0nisKBUA464jZRoEgiGWrSZsDkC7vex4yCKRd2hQeao+GMZ7uuV4lkHzhcffGEaKQnRCIBiMuFk//eVZxQo4Nj7oPkScM7L4lkhDEY6ljLgKkAqqq2A+2KoqzubDvoiB8NF38kpE31JrjsK2itFDef2DyZiCYZHiIShdTzjMtFoaxOdawrvxdVzaMyAtWxJJJ9YHf17gkx6LTYpBEikQjGnASXfCbCXi3xkDRh32IiEskhyEBWTE8CUgGzoihTAKVjkxWhlnXwYokXr05ic8RPl0MUmjNF9p5ILJEMNMYISN3D9t8zTMtlF5K98hqV7IPeChWCqJhua5fhWBKJn+QJwTL97a3gbAZzLBgOQD1TIjkIGEhPyPHApUAa8Pdu7S3A3XvbSVEUE7AEMHbM511VVe8bwHkND9Wb4duHoXAhJE+B4/8IadOHe1YSSRe7N8L/HoCixZA6A45/WKixSSR74HB591moEERiujRCJJJ9UL4KvroHqlbDqGNg/h8CxUIkkkOMgayY/h/gP4qinN2RD9JX2oH5qqq2KYqiB35QFOULVVWXD9TchhxbPbx7OdRuFu/LlosicL9dJCqiSyTDTVsNvH0xNBSK9yU/dF2jUTJ5UhKI3eXpNSfEpNdQ2yqNEImkRxqK4bWzhTw6iDzSxhK45BNRLFYiOQQZjMT0HxVFeUlRlC8AFEUZqyjK5XvrrAraOt7qO17qIMxr6Ggq7jJAOnE0dj3wSSTDTWNx8PVoq5PXqKRHHH1QxzJJiV6JZO80FHYZIJ3UbBIFaCWSQ5TBMEL+BXwFpHS83w7ctK8dFEXRKoqyFqgBvlFV9ace+lyhKMpKRVFW1taO8NoGBouokLonMub+oCOkrsvuGCxC3W1PjLIg5sHCQF6bDpd3n9XSQVRMt0mJXkkvhOw980Dp6ftfq5fJ6pJDmsEwQuJUVX0b8AGoquoB9rk8pqqqV1XVyYh8kpmKoozvoc8LqqpOV1V1enx8fNAYI4qYHDhqjzSYyRdC/JjhmY9k0Aip67I7sblCQro7038DcfnDMx/JgDOQ16a9DzkhJr0WW7v0hEj2TcjeMw+U+DEw5aLAtqPuFs8LEskhymBI9NoURYmlI6RKUZTZQHNfdlRVtUlRlEXACUAPJZ9DBK1ePNClThdhL9ZkUcjQJFeZJSMEnQFmXw2Zc6CxFCJTxDVqtAz3zCQjELvL0ycjxC49IRJJz5isolbI2NOhpUpIpCdP6TlqQiI5RBgMI+Rm4GMgR1GUH4F44Jy9dVYUJR5wdxggZmAB8JdBmNfQYrZCzjxg3nDPRCLpGXMU5Bw13LOQhAB2lxejrrecEFmsUCLZJ5Z4yDt2uGchkYwYBsMI2Qx8ANiBVuBDRF7I3khGqGppEeFhb6uq+ukgzEsikUgk+0FbuweTvi+eEGmESCQSiaRvDIYR8gqiNsifOt6fD7wKnNtTZ1VV1wOyOIFEIpGMUGztHmLCjfvsY9JrcRzMRkhTKfz8Mvg8MOtKKWUtkUgkB8hgJKaPVlX1N6qqftfxugKQ2a4SiUQSothcvVdM12sVvD4Vt9c3RLMaQnYuhOfnQXMZtFbBi/OhoWi4ZyWRSCQhzWB4QtYoijK7s9igoiizgB8H4TgSiUQiGQLsLi/mXuqEKIqCyaDB3u4lMmww1reGiaLv4b3fwFF3QUJHdWtzFHxwJfz6K1CUYZ2eRCKRhCqD8U0xC1iqKEqxoijFwDLgSEVRNiiKsn4QjieRSCSSQcTeh5wQALNeS9vBpJBVtwPeuQSOuKXLAAEYc6oo7rnjm+Gbm0QikYQ4g+EJOWEQxpRIJBLJMGFzeXqtmA5gNmixtx8kRoizGV7/BUz+lZCv7o5GC+POhB//D/KPG5bpSSQSSagz4EaIqqolAz2mRCKRSIYPW7sXU1+MEL2WtoPBCPH54L3fQsI4yDu+5z6Zh8HKl6Bhlyw4J5FIJPvBQRS4K5FIJJLBwO7yYOolMR0OoqrpPz4uktCn/3rvfbR6yDoC1r09ZNOSSCSSgwlphEgkEolkn9hdXsyGQ8QTUrEalj4JR9zaezXrrCNg03tDMy+JRCI5yJBGiEQikUj2is+n4nB5MfVSMR2EJySkjRCvGz64CqZfDpaE3vvHjwZ7PdQXDv7cJBKJ5CBDGiESiUQi2St2txejXoNG07sUrUmvwRbKRshPz4HJCtlH9q2/ooG0mbD9q8Gdl0QikRyEDIY6lkQikUgOEmztnl5rhHRi0oWwJ8TZDN//HY57uH+1P1KmwLYvYM41++ymqiplrWVUtFXQ4mqhub2Zemc9jc5GFBSyI7NZkLmAOHPcAZ6IRCKRhAbSCJFIJBLJXml1egg39u2rwqTX0up0D/KMBonlz0PqVIjK6N9+yZNFIrvbAXpz0GZVVXl/x/v8Y90/8KpeEsMSCdeHE6YLw2KwYNFb8OFjcflinlzzJFdPupoLCy5EkUUQJRLJQY40QiQSiUSyV9r64QkJM2hpdYagJ8TthBXPw7EP9n9fQxjEjoKSpZB7TMAmVVX584o/s7RyKVdMvILsyOx9DlVjr+GZtc/Q1N7E9VOu7/9cJBKJJISQOSESiUQi2SutTjdhfVDGAlGssMURgp6QTe9DTHb/vSCdJE6AXYuDmt/d/i4/VPzAbdNv69UAAUgIS+CW6bfw0c6P+Lr46/2bi0QikYQI0giRSCQSyV5pdXoIM/TNaW42aGkNxZyQn/+596KEfSFpIuz6LqCpzlHH46sf54qJVxCmD+vzUFaDlSsmXsFDyx+izlG3/3OSSCSSEY40QiQSiUSyV1qd7j7VCAEI04dgOFbtdmgsgbQZ+z9G/Gio3ymS2zt4du2zzE2ZS6oltd/DZUdmMzt5Nn9f+ff9n5NEIpGMcIbdCFEUJV1RlO8URdmiKMomRVFuHO45SSQSiUTQ4vD0ORwrzKgLvcT0ta9DzpGg6ds59ohWDwkFIi8E4QX5ougLTsg6Yb+HPHXUqfxQ8QNbG7bu/7wkEolkBDPsRgjgAW5RVbUAmA1cqyjK2GGek0QikUiAJocLU18T00PNE+LzwYa3+14XZF8kFEDR9wC8ve1tZiTNwGq07vdwZp2ZE7JP4PFVjx/43CQSiWQEMuxGiKqqVaqqru74vRXYAvTffz3E1La2s7Swju931FLV7Aja7vH62Lq7hW+3VLOxohmn2zsMs5RIQo82p5vVJY18t7WGXbVt+zVGXWs7yzo/n03Bn09J32myu7H0UaJXeEJCyAgpXwFaA0T3njTeK4njoWgJXp+X93a8x5FpB27YHJV2FFsbtrKpbtOBz+8gpcHm4qdd9SzeVkN5o32v/YrrbHy3tYaVxQ00h6J4gkRyEDKiJHoVRckCpgA/9bDtCuAKgIyM/VQwGSBK6m3c8MYa1pWL+N+MGDMvXTKDvMQIf58vN+3mpjfX4vGpKArcc1IBF83OxNjHFUVJaDCSrsuDgSa7i//7Zjv/WVYCCMnXly+dweyc2D6PUVpv58Y317CmrAmAtGgzL186g/xun89DgYG6NpvsbrLiwvvUN0yvxeHy4vOpfaqwPuxseAeyDutfccK9ETcaGnaysuRbLHoLGdYDvx/otXqOzTyWF9a/wBPznzjwOY4ABvKeWdnk4M731rNkh0jgj7cY+c+vZzA2JTKg3+qSRi55eYVfNOHsqWncddIY4izGAzq+RCI5MIbdE9KJoigW4D3gJlVVW/bcrqrqC6qqTldVdXp8fPzQT7Abi7fX+g0QgNIGB++sKve/L6m3ced7G/D4VABUFf74+RZ21uzfqq5k5DKSrsuDgc1VLX4DBMDu8nLPBxtosLX3eYzvd9T6DRCA8kYHb64oRVXVgZzqiGegrs0muwuLsW+LJxqNgkmvCQ2FLJ8XNn8EmUcMzHhaPcSNZtPal5mZNHNgxgSOTDuSVdWrKG4uHrAxh5OBvGeuKmnwGyAAtW3tPLd4Fy5PV+RBq8PNg59uDrgm31tdzqaKZiQSyfAyIowQRVH0CAPkNVVV3x/u+fTGmtLGoLblu+r9N75Gm4u2Pb6EVVXcICUSyd6pbgn+jBTW2mhx9P2hdn1FU1Db8l0NOD2+A5naIUtjP8KxACwmXWjUCilZCqZIiBy46F9v/Gj0pT8xM3ngjBCjzsiRaUfy703/HrAxDxZ2VAcv7K0qaQz4/m1xutnYg8HR071GIpEMLcNuhCiKogAvAVtUVQ0JPcJ5ecGrNyeNT8agE6uFiZEm4vdw8xq0GlKjzEMyP4kkVMmMDa6nMD0rmliLoc9jzB0VF9R20oSkPlf9lgTS5HARYdL3ub/FqKPJHgJGyMZ3IfOwAR2y0BTGnHY3UcaoAR336Iyj+ar4KxqdwQtghzIT06OC2o4fl0ikuet+ERNu5Mj84O/sjJi+126RSCSDw7AbIcBhwEXAfEVR1na8ThruSe2Lubmx/Gpmhj+M+PixiZw8Mdm/PTnSzFPnTyYhQhgiVrOOJ86bTE68JWCcjRXNvPVzGa/9VMKq4oag49jaPawoauDdVeUs3lZLfT9CUiSSUKGk3sbnG6r4cE0F4XotD5w+DpNe3JpGxYdz/6nj+vUQPCcnlgtmZdCZknDMmAQWjE1k4eZq3ltVzrqyJtxe6RXpK012NxGmfnhCjDoa7a5BnNEA4PXA5o8h8/ABHfZ7Vw2ZTjsa98CKIUQaI5maOJU3t705oOOGOlMzorhyXg7ajg/7rOwYLpydSWFtGx+vreCz9VXsbnZw2/GjKUgSOWFGnYa7ThzDqAQLP+2q591V5Xy/vbZfIZ8SiWRgGPbEdFVVfwBCIIOxi0SrmftOHcvFczNRVZWMmHDCu4UrCGWsVo4fl0RkmB6n28vasiaOyIvD0vEwtba0iSv/u9LvEg4zaHnx4ukclitWcX0+lfdWlXPvx12qKOdOT+P3J48l0tz3BzKJZCRTWNPGRS//RGWTEwCzXsuj507g14dlo9UoVDU7qWiyMz41speRumh2uKlqcnDd/FwUFLZWNbO2rIk739sAgEaBFy6azoKxiYNyTgcTTrcXt9fXLy+SxRQCRkjRYrAkgjW59759xKN6WF2/iXOi0rHs3kRL+vQBGxtgQcYCHl/9OJePvxyDtu+ewYOZZoebwppWrjlqFIoi7ifljQ6ue301LR0qbfEWI0+cN5nRSREsGJuIT4WqJjvvry7nz1901WC5cFYGd544xv8dLZFIBp+R4AkJKSqbHOyqbcPj9eHzqXh9Kppuf8XqFidrSpvIjgv3rx62ODy8sqyEHd0S05dsrwmISbW7vLyyrBinW9w4S+pt/OmLLQHHfmdlOdurWwfx7CSSA6fR5qKwps2/smhr97Crto3dHVLWLo+X4job5Q121pQ2+A0QAIfby5cbq/1GfV1rOw9/uoXSehuFNW002np/uP1uWw2FdTZcHh9ur4/yJiffba1hXIqo2eBT4b6PN1Evc7R6pa6tnSizAaUf6lEhEY617k3IHqCE9A62N24n2hiNKy4Xa8WaAR0bIC0ijTRLGp/t+mzAxw5Vfi5qJNZi5PC8OOaOiuWI3Fj+sbiQCWldixa1be18s6UaZ0fOpt3lISHSzN++3h4w1n9/KmVnbRs1rU4Ka9pCI69JIglxht0TEio4XB4+27Cbhz7dzOycWNKjzby6vASvT+XcaWlcfkQ2LQ4Pj329jVUljdxzcgGLttWwuaqV9Bgztx0/OqBWSFljsLu+rMGB0+3DpAeby4vTHRwyElIa/JJDjtWljdz53nq2V7eRGx/OI2dP5ImFO/h+Zx1xFgP3nTqO7dWtPLuoEINWw28Oz+bo0Ql8t60GgFHxFqakR/Hc4kLq2lwcPTqeu08q4LJ//0xhrY38RAuPnD2RqRnRe52DRlE4enQC/15ajMercsrEFDJjzbR3S0zf3eLE7vLSd+HfQ5Pa1naiw/u3Mmwx6qgbyQaeywbbv4DTnx3QYVftXkVu1Cgc+jhid347oGN3siBzAf/e9G/OyD2jX4bhwUpGjJna1jB+/a+fcbi9nDQhmZuOyeWNFeUB/QqSrBTWtPHUtzuJCtNz04I88hItbKrsEuJMjjRR1ezk6v+upqrZydSMKP54xngKUvruhZVIJP1DekL6yIaKFm59Zx12l4exKVb++UMR7R4fHp/KGz+XUVJn45nvdrC0sJ6zpqbywpJdbK4SXouyBgePfb0Na7cwquM6QkGiw/TEd+SOnDopmagw4WZPjTb7V247CTdoyeohcVciGQlUNjm44pWVbO9QrEmKNPO3b7bz4646pmZEowA3vLkGo06L16ficHt56rudTM2M8udvnDU1lT9+vgUFmJoRTV5iBHd9sIHCWhsA26vbuOKVlVTuowBhdJiBfy8txukWn88P11agKApFdV2eyNMnpZBglTUCeqO6pZ3osP6F/ljNempbR7ARsulDSBgH5r0bsv1FRWVN7Rpyo3JxRGdiaixF47IN2PidjIsdh1f18mPljwM+dihS09rOX7/ejk6rIT7CyKfrq/h6cw1JEXriLUZiwg1MSY9iyY5aluyoIyXShNercv/Hmzl7WqAq2gWzMrjxjbVUNQvP7OrSJm5+Zx1NIz20UCIJYaQnpBdKG+wsL6ynriO0JCs2nM3dVk/mj47nzKlptLV7+XZbLQBxFiPle3g67C4va0oaqW5xUlRro6rFydPnT6GiyUFJvY2Z2TFM7Bb3Hh1m4JGzJvDoV9v4YWcdoxMt/OGUcUHJ7RLJSKG80UFdW9cX9uSMKNrdXs6aksrq0kbmj4knMzacnbWBIYVVTU7GJEWwq86GWafhiV9OprTBTkWTg7HJ1qDQnro2F+WNDlI61OZa7C5+Km7gx511WM16smLDsZp0/phwgG82VzMjK4byxkpOm5TMDcfkYdR15Tk02l2sLG5k+a56chMszB0VS2bsvgv07axp5ceddVQ0OTg8N56pmdH9krINBapbnET1MwctymygtL5pcCY0EKx8CfJPGNAhS1pK0aAl1hyHCjiiM4moXE9z1pwBPY6iKByXeRwvrH+Bw1MHNqk+FFhV0sDPRY2U1Ns4LDeWwjobtxyXT4PNha3dS058OEt31nH7CWNoafeh1yqcOD6Zx/+3jduPH82uOhvRYQbCDFrMOi2H58bxw846JqRaSYsOw7WHYMWWqlYqmxz+xUGJRDKwHFzfmANMTauT619fzbryZm4+Nh8QMdKH54nkcZNOw+lTUrnhzTWcMzWNtGgzZQ0OvD4Vo04TEP4BkBxl5u73N7K7pSsG/qYFeXyxcTdv/lzG8xdNJydBKHi4PF4+XV+FqsI1R+VSUm/j6W93MCYxgtgIuYIrGXlEmnVoNQrejiKdRp0Gk07Dbe+u9/dJjzHzpzMmBOw3NsXKTQvycHt9VDQ5uOWddZQ1CCM+0WpCo4g8jk60GoVwQ5cBsWRnHde/sYbOWoQRRh1XHJkTEPM9JtnKXSeO4aYF+cRHGAMMEJ9P5bXlJTzWrX9BkpV/XTadpMieZbWL62xc+NJP7G4WixMvLCni77+YxFlT0/rzJxvxVDQ6iArv3wNYVJie6m73uBFF5VpoLoO0gavjAbCmZjWjokb5FVbscaOILF814EYIwMykmXxU+BFra9YyOWHygI8/Ullf3sTt7673e0XfW13BMxdM4Za31wUsOPzxjPGU1rXx+opSAAw6DYfnJvDoV9v8fRKtRh47ZxLPXzSNBpsLq1nn9+B2J8Ko65cyn0Qi6R/SCOnG7mYH5Y0OIkx6cuLC2ba7lXCjlqfOn4KiwN0njuHpRTuxmvScOTmVI/LjqG9r56TxyXy2oYrbjh9NcZ2NcKOOv54zkX8sLmRLR0jWudPSqG5xBhggAK8tL+XkCcm0OD2UN9pZV9ZEboKFyiYH//yhCK9P5YedXRVht9e0MkcaIZIRgtvro6jORovDTWq0iftPG0tFowOtRsPEtEge+GhTQP/yRgcur48bjslFoyiU1tuZmxtLTWs7bq+PtnZPgBfxm83VXDQnk/8s7aqifuncLNw+HyuLG4i16Pnn90V0L4be2u6hzekhwqijtd1DpFnP7OwYrCY9sZbgz05Zg52nvt0Z0La9ppXSBjuVTU6Meg05ceGYDV23y40VzX4DpJNHvtjKEXlxxEeY9utvORIpbbST20/va0y4gZqRGo619EkYfRJoBrZmzKrdqzgy4yj/e3tcHknr3x3QY3Si1Wg5IesEnln7DC8e9+KgHGMksqO6zW+AgJC+31nTxphkK3NHxeJTVSoaHbyzspSbFuRz4zF5KAqMS47g7g8D70PVLe1UNTsIN8b7RTDGJEVw4ewM/ru81N/voTPGky7riUgkg4Y0QjpYV9bEFa8KyVydRuG2E0YzIyOKI/MTuOXtdbi8PqLD9Pz1nEmY9Vq27m7h5rfXATAlPYrLDstCr9Xw9eZqqpqdaDUKVx2Zw69mZdBkd/PTrgYKeqjYbHN5mJ0Ty/NLdvHxukoATp+cwm8Oz/avKHfHJas+S0YIdpeHN1aU8ufPt+LxqczOieZXMzN5ZNlWbC4v//pRy/Xzc3llWYk/zvqG+Xk88b8drC8XFYzvPaWAp/63gw/WiGt/Qmqkvw/ApsoWrCYdz104lY2VLZh0Wr7dWkOC1cifP9/Kk+dPxtYeLNag1SjcuCCPVqcHryryQk6fnNLjeXh8alAYxs3H5nPvhxvZ2rE6etHsTG48Jo+4jgWAPfuLv4cXjzf4MxvKlNTbOGxU/9L3o8MMNNpduDw+DLoRlHZYXwg7/wdnPj+gw9Y4amh2tZBq6coxcEamonO2YGitxhUx8FLQh6cezhdFX7C6ejVTE6cO+PgjkT1r+xj1GmLDjSREGHl8obhf5CdaOH9mBj8XN/LMokJA5F+ePCGZfy8tDtjfsYfwS4RJz63HjebkCcnUtbnIjA1jdGLE4J2QRCKRiekAzXYXd3+wAZ1W4ap5ORyZH8fLPxThcPt45Mut/geORrubBz7ehN3l5atN1f7915Q1ERdu5J2VZf6HLa9P5ZnvCmm2e/jb19spqrMRE2bAuMeX8jnT0thU2czW3S3MyYllakYUH6+rZHt1G8ePSwjom2g1kpsgc0IkfcfrUwetMN/WqlYe+nQLng5j+VczM7nz/Q3YXJ1SmF6e+N8Ozp4mQpSyYsOobHL4DRCDVkOzw+M3QAA2VDRT2eQIEGDIjA3H5vTg8fr4atNu7C4PcR0hQk8u3MH5MzMC5qVRYFyKlYc/28IT/9vB09/u5FczM9BpNLi8XvYkLcbMmZO7HiDHpVjZVNHsN0AAXl1ewurSrmrVY5Iigj7Lv52XTVLkweMFUVWVknr7XkPS9oZWoxBvMVLWaB+kme0nC++HglPBsO9cn/6yavcqcqNz0XQvd6VoaEsYTWTZzwN6rE50Gh2njTqNx1Y+hqoeXIbv3siJF7lenVQ3O9Fo4NP1Vf627dVtbKpopqq5y5v69eZqkiONhHUL4TTqNOQlBn+XRoUZmDMqjlMnpTAxLQpjP+rjSCSS/iONEKDB5uIX09K4YGYmy4saiAk3ct8p41hX3sye9/fKZmeP8pMqsK7j4SqgXVU5e2oqNx+bzxsrSvjL2RM5enQ8eQkW7jhhNONSrOxubud3C/LxqSoRJj2/P7mAXbVt3HvyOK6fn8uo+HB+OT2Nf182k9Ro6RqW9I7Pp7KyuIEb31jDBS8u55N1lTQPcO2GPcUXnG4fdpc3qC09ykxugoWzpqayurTJvy3BaqS4PlhBaHVpE2dNSSU3wcJ1R+dy2uQUNu9uZWlhPbNzYrjnpAKK68UD7s5aG2aDhvtPG0tBcgSzsmP4xwVTibcamJkdzfhUK0+dP4WMmDDu/mADv3xuOW+uKKWmtSss0qjT8rvj8rnluHxGxVs4d1oaq7oZHJ1s3d0lSDE2JZLXfzuLYwsSyEuwcN+pYzlvRsZBJZta2ezErNfuV7J9arSZHSOpptGuRVC+AsaePuBDr9i9gvyovKB2e1w+UcXLBvx4ncxJmUObq43Piz4ftGOMJNqcHp7+1VSOG5vIqHgLd55QwJaqlqB+y3Y1BBU33VDRwu9PKiAvwcKR+fE8f9E05o6KG6qpSySSvSDDsQBruI6dtW282hELurasia83V/Pg6eOC+iZECNm/PQkzaBifYmVjZeBNMT8pgs82VLGlqpXM2DAe+3ob+QkW/u+Xk7n83z9z1Oh4pmZG8YdusfPf76jl2QumkhoTxs3H5vPbI3IIM2jRaaXNKOkbGyuaOf/F5bg7woNWFDfy13Mmcu709AE7RkpU4Kp/fIQBk14TUN/GqNOQm2DhX5dMx2rSs7u5ncJa4WGobW0no4d464lpkbg8Xs6ckkpChJGHP93sl7teX97MiqIGblzQ9dB31/sb+fjaOZw0PgmDVutPpH7lsmi8qkpVk4Mzn11Ka0fY1pqyJn53bB43zM/zGw3p0WFcPz+PS+ZkodMorCtv5oM1FQHzyt8jNGNaZgxPXxCJy+M7KJNXN1U096oQtjcyY8NZXdrECeMHriL5fuNogo+uhZlXgm5gPVV1jnpqHbVkWDOCtrUljCFxw/sonnZU3cDn8WkUDecXnM9ff/4rh6ceTqTx4K5nYTXrOee5ZdwwfxQnT0zm8/UVHDUmKajflIyogMWOzrYP11ZwxpRUKhrtXPPaaj64Zi6jk6xB+0skkqFDPtUC1U3tvPVzYHGjZoebZrub3x6Rg7ajiEG4QcvvTxmL1+djZlaXxvzoxAjSosM4Z3pagIFy7vQ0Whxu5o9JYFt1K19s3E2DzcXFc7NYuKWa6tZ2qpqdvL/Hw45PhVUlYiVWURSsZj3tHh9rShv5cuNuNlU04/IEh5VIJJ2sLGn0GyCd/GNRIc0DqHk/JsnKzcfm07n4X9Hk4Pr5ef4wJYNWw7VH56JRID02HFWB0UkR5MSJB9t2jw+zQcvRo+P9Y+bGW5g/Jp5nFu/ir19tQ6tR/AZIJ+vKm/1FOxVF5G/kxFtJsJoDlJxMBi3hRh1bdrf4DZBOnlu0i/XlzXy5cTcbK5pp7ygkajXrCTPquHJeDukxXWFIZ0xOYUoPBRKNOu1BaYCAKDyZHbd/ntfJ6VF8tr6K9uG+T/l88P4VkDIF0mYM+PA/7f6JvOh8tEpw2I7PEIYzKp3I8lUDftxOcqNymZY4jfuX3n/Qh2WNSbZy63H5PPVdITe+uZbaNhcJFgPHju0KW06PMXP+zAx21nSFUk7PjMas16LXavjrV9t4fUUZdpe3Ry+KRCIZWqQnBNBoFHRahT0iSWiwu1iyvZbr5+f6H5yeXLidnbU2bj8+n1/NyiTMoCUnLpwWp4fnFxdy1tRUzHotOo3C4u11zMyK8SfGNdldpESHkRUb5o8vd/tU9D14OMzdYlEdLg//+rHILyGqKPDYOZM4a2rqQRX+IRk4dJrg68Kg0wzo9WIx6bhiXg7HFCTQZHej0yjc8s46rpiXg4rIzXhnVRmH54qwB40GPl9fyaycGE6dlIKiwNrSJo4fn8j184VEb3Z8OEadwuu/mUWj3R2Ud9FJlFnPa7+ZRVSYnlHxFkz7iN3WaILH0OsUPlpbwcs/FqMo8MiZEzh3ejqajr/bmGQr7141l6I6GyadhlEJloPW2NgbP+6s57RJPSfz98aoeAvZceFc89/V/POS6cN3n/r6HmithAUPDvjQKirLKpYyL33eXvu0JY4lunAJTVlzB/z4nZyVdxaPrHiEf2/6N5eNv2zQjjPcWIw6fntEDkePEfebzGgz76+pJC8hgpMnpODy+lBVlb9/tY2zpqZia/eiKEJVa2NFS5Bkfk/3BYlEMrQc8kaIqqrEhRn4zeHZPNlNpjM50oTd5WVbdSsxFgMnTUjiF88v9xdOe/Sr7fz1nIkcN04ktDbaXZw5JY1nOxQ5AOIjjKRHhzG5hxXUBWMSeX7xLlYUNXDHCWNYUdTg32bUaTimoEtRZWdNW0ANA1WF33+4kamZUWTHyUR1STAzsmMIN2j9SeIANy7Iw9rPwnO9YdJrGZciwkBanW7GJlsD5G6Pyo9nVIIw4MP0Os6cmsad72/wbzfqNJw9NY2pmYGfkTmjRPjK7mYHc0bFsqywPmDMgmQrCda+hdaMS7YSH2EMqOJ9/owMPlwrPJCqCvd+vInpWTGM6ib8kGg1kdjHYxxs1LW1s6u2jdFJ+68OdOWROdz70Sa+3VoTcD8bMpY8Btu+gOP/BNqBNyBLW0qxeeykRew9xLE1eQJZS/4PxetC1Q5OwTuD1sC1k6/lLz//BYvewrmjzx2U44wEjHotGTFhxIR7iLMYmZIZxZWvrgrIRfv7LyZx9wcb/GGheq3C8xdN89cNAYgNNzA+RYZiSSTDzSFthFS3OHh7ZTn/+rGYq47M4dGzJ7Bkey25iRFMSI3k8w1V/PGM8czLjyM9Jpw3fjubbzZXU9Zo58RxSczIivGP1erwsKWqlVuOy2djRQtJkSZiwg1UtTh6PPaEtEjevnIOn2+swtbu4Z8XT+e7bTVYTDpOHJ/MxLSu+N56W3AIjcPtHfBEY8nBQ0GylbeunMNXm3ZT29rOSROSmZ4VbAwPJBEmPdcdncuEtEg2lDczLtXKUfnxRJrFw5fD7WXh1mruPqmADeVNmA06cuLDWV/eyPHjg2O7AZIizdx7ylh+2FHH6tJGpmdGc1heXJ8NEICsuHD+e/ksFm6pZldtG4fnxfHR2kqqW7qMknaPj8YBDFULdb7eVM2k9KgevbR9RafRcMyYBN5fXTH0RsjSp2Hlv+D4P4JxcGRWF5UvZnzsuEBVrD3wmKNotyYTWfozTdmHDco8AGLNsdwy7RYeX/04O5p2cPO0mzENcP7LSGBFUT1/+nwLhTU2Lj0sk0iTjmcvmMribbU02l0cOzYRl9fH0+dP5atNuzHoNJwwPokJaRG8ePE0vtq4m6y4cBaMTSSnn/VvJBLJwHNIGyGfrKvyV1X+0+dbMek0fHTdYf5ktT2/OAuSrRQk97x6EhdhAFQeX7iDnLhwVhY3UG9z8f7VPbvhFUVhUnoUk9Kj/G0Lxvb8RZ0WHRZUgT3RaiS5n9KZkkOL8amRQSoxg0lNi5Nr31hNfZuLtGgzP+6s480VZbx/zVySI81EmPRMSInkT59vIScuHKfby9sry3j+wmn7HHdfn7u+Mjopwr+qX1Rn454PNgZsj7MYSI2Sn6dOPlpbMSDqQZPTo3h31UZ8PtUf6jborHgRlj0Nx/0RwvpX46SvOLxOVlSt4JJxl/TatyVlMrHbvh5UIwQgMTyRe2bdw+tbX+eUD07hmsnXcGrOqegHwQs0HGyvbuWil1b4vwefWVTIo2dN5NJ//cxR+fEkR5m49vU1XDQ7g/tOGRf0fXrs2CSOHdvzYodEIhkeRkRQpKIoLyuKUqMoysbeew8MTXYXry4vCWhzenwB9T8AqlucLNxczes/lbCssI62HgqjAYQZdNx1UgGT0iLZUdNGu8fHX86eSEHKga/CjYoP5/mLphHfUSgtMzaMf1wwjcSDqCaBJPQpabBT1uDA7vKyvboNm8tLVbOTkrquehFnTU3j1InJFNXbqGtzcf38XGZk989D43B5WFHUwOs/lfD1pt0BNQH6QlZsGC9cNI2Ejs9TeoyZ5y6cRrI0QgARirWpspnJ3RZI9pdYixGTXsOuurbeOw8Eq1+BJX+FYx8CS0Lv/feTH8q/J9OagdXQ+/29NWUSkRVr0DmaBm0+nVgMFq6YeAWXjb+Md7e/y3HvHcdLG17C5g6Wwg41dta0BizE+XzinnP9/FyW7arnjRVlzB+TwC9nZqAbSUUyJRLJXhkpnpB/A08DrwzVAY06LcmRJkrqAwtqxUd0xe022Fz8/oONfLOlyzC579SxXDo3q8dEy/zECP512UyqmhyEGXU9yo/uD4qicNToBD6+9jCaHG7iLUZ/5WaJZKQQbtChKATV1gnvVmciPSaMR8+ZxA3H5KHVKGTEhPVbevqzDVXc+s56//vZOTE8ef4UEiL6ZpQrisLhefF8fN1hNNrdxFkMxPdx30OBbzaLUKyBqnaelxjB6tImchMGufr0+rfhfw/CsQ9DxOCteHt8Hr4s/pKTs0/pU3+f3kxr8gTitnzB7qnnD9q8upMfnU/+tHxKW0r5svhL/rPpP9w49UbOyjsrZMVMLMZgj45Oq7B0Rx2XH56NTquwvqyJNkfPC4USiWTkMSKWC1RVXQI09NpxADEbtNx0TH6AilBSpJGZ2V3u+227WwMMEIC/fLk1yHDpTqRZz5hk64AZIN1JjjJTkGyVBohkRJITH8ZvDs8OaLtkTiaj4gNrTZgNWvISI8iJt/TbAKlscvDQp1sC2pbvamBLZf/lNpMixedJGiCBfLVxN1PSBy5/KCs2nDU9FH8cUDa8C1/eCcfcD5Gpg3qoxeWLiTZGk2Lpew2Uxqy5JG78EMU7tHl8GdYMrph4BTdMvYFXN7/Kb7/5LXWOuiGdw0AxJimC2TldeZgmvYYwg46fiht5dlEhT/5vJ4u21/H4/7Zjd0lDRCIJBUaKJ6RXFEW5ArgCICMjuDDU/jAzO4b3r5nL5soWwgxaJqRFkR3X9cBk6yH0yun24XDLGh0SwWBcl6GKSa/jmqNyOSIvjpJ6O+kxYUxMiyRsPypu7w2n20uLM/hBrq1dfib3ZH+uTafby4riBi6YnTlg8xgVb+HtlaW9d9xf1r4hpHgXPADRAzfvnrB57Hxc+DFn5Z3Vr/3aI1NxWeKJ3bGQujEnDtLs9k6mNZM7Z97Jx4Uf84tPfsGT859kfNz4IZ8H7P89M8Fq4v9+OZn15c3UtrZTkBTBj91U8zqpbHLS7vERNjhiZBKJZAAJGSNEVdUXgBcApk+fPiBVmTQahYlpUUxMi+pxe058eJDM6azsGNKiZey4RDAY12UoEx1uYF7+4MXiJ0eaOX5sEl9u2u1vE1XZ96+y98HM/lybywrryY4LxzKAhmNWXBiFtTacbu8+67n0G1UVKlhLnxQhWFF7l8odKN7a+hajonJJDOu/2ld97jGk/PwK9bnHoOqG/glZq9FyZt6ZZFozueqbq3jgsAc4JuOYIZ/HgdwzkyPNAYIsbl/w7hfOziBaWiASSUgwIsKxRio58RZeuXwW0zOjCTNoOXNyCn88c8IhV7RMIhkpmA1a7jhxNOfNSCfcoGVSWiSv/Hom+YmDnG9wiPD15t1M2suizP5i1InaDhsrmgduUE87fHIDrHoZTnhkSAyQFbtXsLF+A0emHblf+ztis2m3JpO89s0Bnln/mJo4lRum3sCDyx7kv5v/O6xzOVAmp0fy7AVTyYgJIypMz83H5nH6fhbYlEgkQ0/IeEKGi2mZ0fz7shm0Oj3EWAwYdQO4kieRSPpNdpyFh84Yz43H5BFu1A14AcZDFZ9PZeHmGu48ccyAj52fGMHyXfVM71Zbab+pL4R3LgWjVRgg+oHPv9uT7Y07eGXzK5ybfy7GAyg6WDPuNLK+f4KmzDnY4/MGcIb9Izsymztn3smTq59kV/Mu7pp5V0hK+Zr0Ok6akMzsnBhcXh+JEaaQTbyXSA5FRoQnRFGUN4BlwGhFUcoVRbl8uOfUHYtJT3KUWRogEskIQa/VkBxllgbIAPJTUQPhRi0pgyBVPDbFynfbag9sEK9HhF+9OB8y58CRdwyJAbKqehVPrXmSU3JO2a8wrO54zFFUjz+D3C/vRd92gH+PAyTOHMedM+9kZ9NOLv7iYspayoZ1PgdCTLiRJKtZGiASSYgxIowQVVXPV1U1WVVVvaqqaaqqvjTcc5JIJJJDiX/9WMSRo+MHZezxKZFsr26loql/NV0A8Hlh88fwjzmw8T044S8w5lQY5AfOBmcDL2x4kde2vsZZeWeTZc0akHFbUybRlDmHgg9vxFy3c0DG3F/C9GFcO/laxseN57zPzuPZtc/S5hqimi4SieSQR4ZjSSQSySHOd1trWFPayPkzJw3K+AadhqNGx/PYV9v4+y8m9b5i7XZA1XrY8TWsfwsM4TDxPEibMWjGhw+VWnstOxq3s6p6FdsatzM5fhKXjL30gEKweqJx1Dw8pgjGfHIbjdmHU1twIrb40aAZem+7RtFwXNZxTEmYwoc7P+S/W/7LsZnHMj99PhPjJxJtGji5ZolEIumOou5ZWSwEUBSlFijptWMXcUBoiqP3HXmOg0Odqqon9KXjflyX+0uo/K9DYZ6hMEcInmefr0vY+7WpGMyatOtenaTRmzReW5Pb3VCxH66K3lF9Hr3GEOY1JudZPM017RXP/Xpj57bfTNFHv3iaOWdv+1a2+lyFDT7ngE3GoNEo2WGWXvs5vV7VN7hfkFZUZZLG26Pl8Wt3hH2RagjQiVd9ql7RKINabEQbodWZUkz7jHMrfbp0R8vKlr0V5zGpqton/d9+3DND5XO6N+T8h5c4YGt/7pmSoSEkjZD+oijKSlVVpw/3PAYTeY6HDqHydwiFeYbCHCF05rk3QmH+co4Dw2DMMRTOe1/I+Q8voT7/g5kRkRMikUgkEolEIpFIDh2kESKRSCQSiUQikUiGlEPFCHlhuCcwBMhzPHQIlb9DKMwzFOYIoTPPvREK85dzHBgGY46hcN77Qs5/eAn1+R+0HBI5IRKJRCKRSCQSiWTkcKh4QiQSiUQikUgkEskIQRohEolEIpFIJBKJZEiRRohEIpFIJBKJRCIZUqQRIpFIJBKJRCKRSIYUaYRIJBKJRCKRSCSSIUUaIRKJRCKRSCQSiWRICUkj5IQTTlAB+ZKvoXj1GXldytcQvvqFvDblawhffUZel/I1hC/JCCQkjZC6urrhnoJEEoS8LiUjFXltSkYi8rqUSA5tQtIIkUgkEolEIpFIJKGLNEIOAbw+L/WOepweZ5/6N7c30+Jq6fdxbG4bjc7Gfu8nkdTaa6lqq+pzf5/qo8HRgMPjGMRZSSRDS+e9ut3THtCuqqq43t0OGhwN2N32YZqhRCKRDBy6wRxcUZR04BUgCfABL6iq+sQefY4CPgKKOpreV1X1wcGc16FESUsJb2x9g6+Lv6YgpoCrJ1/N+LjxPfZtcbWwqGwRL6x/Aa2i5apJVzEvbR7h+vB9HsPtc7OiagVPr3maemc9FxRcwEnZJxEfFj8IZyQ5mGhtb2VJxRJe2vASDo+Dc/PP5bis40iLSNvrPuWt5byz7R0+LfqU3Khcrp50NZMTJg/dpCWSQaC4uZjXt77OwpKFjI8bz1UTr2Js3Fgq2yr5YMcHOLwOfD4fX5d8TYolhesmX8f0pOloFLmWKJFIQpNBNUIAD3CLqqqrFUWJAFYpivKNqqqb9+j3vaqqpwzyXA457G47f1nxF76v+B6A2opa1tau5Y2T3yDDmhHUf0XVCu754R7/+9uX3M4zxzzDvLR5+zzO5vrNXPO/a/CpPgAeW/kYAJeMu2SgTkVykLKqZhV3fn+n//3/rf4/jDojFxRc0GP/dk87z659lk92fQJAjb2GNTVreOPkNxgVNWpI5iyRDDQ2t40/r/gzSyuXAvBd2XesrlnNaye9xutbXufHyh+Znjid93a8B0C1vZorv7mS1056jbFxY4dz6hKJRLLfDOoSiqqqVaqqru74vRXYAqQO5jElXVS0VfgNkE5aXC0UNRcF9VVVlXe2vRPU/mnhp70eZ33ter8B0sl/t/yXBkdDP2csOdT4seLHoLb3d7xPk7Opx/677bv5rOizgDaHx0FhU+FgTE8iGRLKW8v9Bkgnze3N7Gjcwdvb32Ze2jy+LP4yYLtH9bC9aftQTlMikUgGlCHz4yqKkgVMAX7qYfMcRVHWKYryhaIo4/ay/xWKoqxUFGVlbW3tYE71oMGgMWDQGILaTTpTUJuiKCSEJQS19yWkyqK3BLXFGGMwaIOPfbAhr8sDI8oUFdQWY4pBr9H32F+v0ROmCwtqN+vMAz21kEdem6GDUWvs8Zo368xYDVZaXa1YDdYet4cag3FdqqrKb19Zya7atgEZTyKRDA1DYoQoimIB3gNuUlV1z4zn1UCmqqqTgKeAD3saQ1XVF1RVna6q6vT4eJlr0BfSItK4ZvI1AW0zE2eSG5XbY/9zR58bYLSYdWZOyj6p1+NMTphMvLnrf6KgcN2U67AYgo2Tgw15XR4Yc5PnBjxcaRUtF429iHBDz3lIKZYUbpp6U0Db2Jix5EfnD+Y0QxJ5bYYO6RHpXDXxqoC2OclzKIgt4Nbpt7KwZCG/GP2LoH3GxoReKNZgXJdVzU6+2VzNt1trBmQ8iUQyNAx2TgiKougRBshrqqq+v+f27kaJqqqfK4ryrKIocaqqSgHxPbC77bS6WokyRmHUGXvtr9VoOSf/HCYnTKbOUUeEPoLsyGxizbE99p8QN4FXT3qVVbtXodVomZo4lTExY3o9TnZkNi8d/xJratbQ0t7CpIRJjI/tOfldEvo0tTfh9rr7LDzg8Xmod9QTpg8jwhARsG1K4hSePuZp1tWsw+lxMilhEtMSptHqasXuthNrjkWnCbxNnZxzMhnWDDbVbSLZkszk+MkkhicO2PlJJAOFzW2jzdUmvHvanr17AA63g6PTj2Z0zGi2NW4j05rJpPhJxJhiWJC5gMSwREpbS/n7UX+nuLmYhLAEJidMJt2aPoRnM3IprrcBsKvWNswzkUgk/WGw1bEU4CVgi6qqf99LnySgWlVVVVGUmQjvTP1gzisU2VS3iSdWP8H6uvUcnnI4V02+aq8eje40OBv4YMcHLCxdyOjo0dw87WaSLck99m12NbOhbgNvbHsDBQWTzkSqJTXowbEnsiOzyY7M7vd5SUIHp8fJ9+Xf8/fVf8fmsnHR2Is4I/eMfRojZS1lvLrlVT4t/JT0iHRumX4LM5JmIG4NgikJU5iSMAUQYRU/7/6Zv638G2WtZZwy6hQuKrgo4GHLYrAwJ2UOc1LmDN7JSiQHyNqatfzfqv9jW+M2FmQs4PIJl/d4j1xfu55/bvgnK3avYEzMGG6YcgNTE6f6t5t1ZmYmz2Rm8syhnH5IUdPSjk6jUNUsJbslklBisMOxDgMuAuYrirK243WSoihXKYrS6Xs+B9ioKMo64EngPFVV1UGeV0hR0VbB1QuvZlnVMmxuG1+VfMVdS+7aa/JuJ22uNh5e/jAfFX6EzW1jdc1qrlx4JcXNxT32X1a5jIeXP0xZaxmlraXct/Q+ft7988CfkCQk2VC7gZsX30x5azmN7Y08ueZJvi7+eq/9XV4X/1j3D97Y+gat7lY2N2zmyoVXsr1x78m02xu3c9XCq9jcsJlWdytvbH2Df6z7By6vazBOSSIZFIqbi7nymytZXbMam9vGR4Uf8cflf6TNFZizUNVWxQPLHuC7su+wuW2sql7Fjd/dyLaGbcM089Ckrq2dzNgw6tvkfUIiCSUGWx3rB1VVFVVVJ6qqOrnj9bmqqs+pqvpcR5+nVVUdp6rqJFVVZ6uqurS3cQ81SlpKaGwPLAK4tXEr5W3l+9yvylbFit0rAtpsbtte1bHe2/5eUPtnuz4LapMcmux5LQG8ue3NvRa27EnJyuPzsKt5116PUdhUiNvnDmj7rOgzdtt378eMJZLhoai5CLsnsKDgT7t/osoWWJCzuKU4yChvam/q8R4t2TsNNhcpkWaaHO7eO0skkhGDrHIUAvSkBqRTdL0qoxi1RkzaYCWsnooPKopCekRwfPG+isZJDi3izHFBbcnhyT0qsAGYtCYiDZFB7T1dz530JGYQZYzq8TqWSEYqPd1jTVoTRm1gLl+YPgydEhwV3VuBWEkgjXYXSZEmmuzSEyKRhBLSCAkBRkWN4pScwFqOv534WzIiggsOdictIo0bpt4Q0DYvdR550Xk99j87/+wAw8ait3BC1gn7OWvJwcaMpBkkmLtknHUaHVdMvKJHyWeAhLAEbp9xe0DbxLiJ+xQ7GB09molxEwPabp9xe4/y0RLJSCU3Opd5qYFFXm+cemPQQk9+dD4Xj704oO2Y9GMYHT160Od4MNFkdxMfYcTW7kVGc0skocOgq2NJDpwIQwS3TruVE7JOoNJWSaY1k3Gx4/aptuL2uam117IgYwEFMQXsaNpBUlgSedF5ODwOjG4jYfrAFenxceN585Q3qWytFJ4RSzp6rZ56Rz1GjZEqexUR+giSLEkDen7VtmpaXC0khSURYew9CV4yeLi9bmodtZh1ZqJN0QHbcqJyeOn4l9hUvwmnx8mYmDEUxBYEjVHvqKfeUU+sKZYFmQvIsmbR4GzAqDOSac0k2hTNtvptaDVacqMDxRUSwxP521F/o6SlhHZPOzGmmKA+EslIJ8YUw31z76OkuQSH10GcKY4wfRiNzkacXicmrQmHx0GUKYpfFfyK8XHjKW0tJSk8idzIXL9h3+5pp94plOWijFH++7pJZyLGFLNfc6u11+JVvSSEJaBRDo51yBanG4tRh0GnYHN5sRjlo41EEgrIT2qIEBsWy5FhR/apb3lrOf/e9G/e3/E+ceY47phxB2fnnc22xm3c+f2dbKjbwMykmdwy7RbGxHatSjc4GlhctpgX1r+ARtFw0diL2Fq/lY31G7ls3GV8XPgxDq+Dm6fdzLzUeWg0B/YF5vP5+L7ie/5v9f9R3FzMYSmHcdWkq5gQP+GAxpXsHyUtJby04SU+2fUJyeHJ3DXzLuakzAmQyM2KzCIrMmuvY6zcvdKv4jY+djw3Tr2Rz3d9zkeFH5FqSeX3c37Pq5tf5Z3t72DWmfnNhN+wIGOBX7HN6/NS2FTIn3/6MxVtFZyYfSJXTrySzMjMwT59iWRAKW0p5em1T3Nc5nE8tfoptjdt5/DUwzk772xe3vAyG+o3MDVhKrfNuI1js45lZ+NOnlj9BEsqljA6ajR3zrqTt7a9xdfFX/uV5dbUrOE/m/9DgjmBO2feyWGph/W5KGybq42vS77midVP4PA4uGTcJZybf+5B4WVsdXgIM+gIN+pocbilESKRhAgHxzKIxI/X5+W1La/x1ra3cPvcVNmq+N2i37GmZg3XLryWdbXr8Kk+llct53eLfketo6ti7Y+VP/L3VX+nzd1Gi6uFZ9Y+w5jYMdQ763nk50c4NutYipqLuGXRLayrXXfAc91Qv4FbFt9CYVMhXtXLkoolPPrzo9TZZYmYocbldfHCuhf4YOcHeHweylrLuO7b69jasLXPY+xq3sWd39/J2tq1+FQf6+vWc/uS2zHrzXhUD82uZn6o+IFXNr+Cw+OgwdnAoz8/ypraNf4xtjdu59r/XUtJawke1cMnuz7hqbVP0e5pH4zTlkgGhV1Nu7h64dVMTZzKU2ufYmvjVnyqj/SIdB5e/jDr6sR9eGX1Sm749gbKWsr4w9I/sKh8ET7VR4QxgufWP8fnRZ/jUT0UtRRx03c3YdKZ8Pg8VNoqufG7G9nSsKXPc1pbu5b7lt5Hg7MBh8fBc+ueY2HJwkH8Kwwdbe0ezAYtZoMWW7tnuKcjkUj6iDRCDjLqHHV8uPPDgDYVlZ1NO2l2NQe0l7eVU9FaAYBP9QXtB0LDPi9K5JA0tzdj1Bpx+VwUtxQf8FyLmopo9wY+XK6tXUtZW9kBjy3pH7X22iAlK5/q65dKT2lLKdX26oC2eme9P8l2auJUllYEi9+tqOpS3SpqLsKregO2f138ddC4EslIpqSlBKfXiVbRYnN3FdCz6C0BCz8A1fZqilqK2Fi30d82OWEyyyqXBfTzqB48vq4HbBWVXU17V5rbkx8rfgxqe2/He9jd9h56hxY2lwezXkOYXkerNEIkkpBBGiEHGWadmaTw4JwNq8GKT/UFtGkVrf8BUaNoyInMCdovISyBBmeDf+xO+dS+FDDsjZ7GsOgt+1RPkgwOJp2px6KDVoO1z2NEGCKCYswVFLSKFhC5Ij2FfiSHdxXP7OmaiDXH7jX5XSIZiXSqvHUPZQRxz1VQAtoUFKwGa4AoSGeV9T3p/Cx10p/7cKolNagty5q1V3W7UMLh8mLSazHpNdITIpGEENIIOciwGq3cOv3WgC+rMTFjmBg3kQsLLgzoe/Wkq8myZvnfn5l3JhH6ri+1KGMUqZZUqu3VZFmzsLlt+FQfc1Pm7lPhqK+MiRnDYamHBbRdM/kaRsdIZZihJtYcy10z7wp4QJqaMLVf/+fRUaO5YMwFAW3njzmfHyvFCuy62nUcl3VcgNxuYlgiM5Jm+N+PiRnDzMSuytAKCnfNvOugiFuXHDrkReVxfObxrK9dz/yM+f72Hyp+4JejfxnQ97cTf8uYmDHcMu0Wf9sXRV/w2wm/Deg3M2kmFW0V/vdjY8YyLnZcn+c0N2UuiWGJ/vdmnZmLx12MThva+ROqqmLzGyFa2pzSCJFIQgUlFOXspk+frq5cuXK4pzFi8fg8bGvYRmFTIRaDhYKYApItyTS1N1HcXEyrq5VIYyRx5jg8Pg/xYfH+VbhdTbvY2rAVRVFIDk+moq0CvUZPtCmaHQ07iDJFMS5uHJnWgUkULmkuYXP9Zuqd9WRaM5kYN5FIU3BtiWFE6b2LINSvS7fXzdbGrexq2kWkMZIxMWN69KrtbtuN2+cmyZKEXhOo0FZtq2ZD3QaqbFUkhScxNmYs9c56djXtItoUzdiYsRS1FlHYWIheqyc/Op+J8YGSvDW2GrY0bKHR2UhOVA4FMQX7VILrCVVVqbJV4VN9JIUnBa1IHwT0+bqE0L82Q5F6Rz2b6zfj9rrxql5aXC3EmGIwaA04PU6a25tJjUilIKYARVGotddid9vZ1bzLvwDU1N5EWWsZ0aZoRseMpt5R33Vfjy0I8CL2hE/1iQKJKiRbkilvLWdLwxY8Pg950XnkR+cPxqkP6T2z3eNl3L1f8erls3hucSGnTUrh7GmyvpUkiH7dMyVDw0H3zSwRIQDj4sYxLi5wlayoqYgHlz/IzqadjI0dy1l5Z/HYz48Jpazpt5ATleN/dTI5YbL/9+4r1gOBT/VR3lbOE6ufoMJWwaykWdwx846RZoQcMui1eibETWBCXM/qZG2uNj4r+ownVgl1nbPzz+by8Zf7la0Aauw1vLDuBbY0biE/Kp9759zLpIRJAYZGfHg8M5Nm9nQIABLCE0gI33/PR7OzmQ8LP+TZtc/i9rm5YMwFXDj2QhLDE3vfWSIZIGLNsRyRdkSv/bbUb+Hh5Q+zvm492dZs7px5J+9uf5dvSr8hOTyZe+fcy9yUuWgUDUnhSUH39b3R4Gzg7W1v89KGl1BRuWzcZZw3+jyOzzr+QE9tRNEZigVg1Gmwu6QnRCIJFWQ41iFCeWs51317HTubdgKwuX4zL65/kdNzT2dJxRL+tvJvODyOIZ1TYVMh1317HRU2EWLw0+6fuH/p/bS2tw7pPCR9Y13tOh5e/jCt7lY8qoe3tr3FJ7s+8W/fbdvNDd/dwJZGodizvWk71397fUAIyVCwumY1j618DLvHjtvn5t+b/823pd8O6Rwkkr5Q76jn1sW3sr5uPQBFLUX8btHv/JLUVbYqrv/2ev99uz8sr1zOM2ufwel10u5t57n1z/FjVXByeqhjd3kx6cWjjDBCvL3sIZFIRgrSCDlEKG8tp8XVEtBWba8myhgFwJKKJdTYa4Z0TiUtJQFqLwDr69az2757SOch6RurqlcFtX208yOa24XqWkVbBXWOQHnlxvZGvwLbULG4fHFQ2wc7P8DpcQ7pPCSS3qiyVVHaWhrQZvfYA3L6PD4PJS0l/R7786LPg9o+Kfykh56hjd3lwdzhCTHoNNikESKRhAzSCDlEsBqDVY66x8knhCUMuSpVpwHUHavBGlTJXTIySIsIjrMeFTXKn2huNViD1HsUlB6vvcGkJ5W3MTFjgvJXJJLhxqK3YNQag9r3zGGKNPY/RLUnUYmCmIJ+jzPSsbu8GHSdnhBZJ0QiCSWkEXKIkBOZE6S28qsxv2Jh6UI0ioZ7Zt3To0TrYJIXncepOacGtN096+4epSQlw8/0xOnkWLse8Dsrnht14iEqy5rFdVOuC9hnTwW2oeCI1CNIsaT430foIzhvzHloNdp97CWRDD0Z1gxunX5rQNsvR/+SFbu7aueclH0S+VH9TyA/Put4Yk2x/vfRxmhOyTll/yc7QgnICdHLnBCJJJSQiemHCCadiUvHX8r0xOlU26tJDk8WCeyxQukqP0Z8ybm9biraKlBQiAuLo9pWjVFnJEIfQa2jFoveEpDgW22rps3dRoI5gQhj3zXrGxwNNLQ3cM3kazh11Kk0OBvIiMiQ8rwjmAxrBs8e+yyb6jbR7m1ndPRo/3UDIrH9vNHnMTt5Ni3tLVgNVrIis/D4PBQ2FRKmCwtIYu/Ep/qoaK3Aq3pJDk/2GzX7S3ZUNi8f9zLbGrf5VYCyI7MPaEyJZCDpvP+ZtWZmJs7kn8f9k8q2SuLN8SSGJeLyuShvKydcF05CWAJOb/9CCd1eNwaNgWePeZZKWyUqKvlR+f5ck4MJh7u7J0RDQ5trmGckkUj6ijRCDiG21W/jwWUPUmGrINuazUOHPcRJOSf5t1fbqvnXxn/x1ra3QIGzcs/C4XEwNnYsn+z6hM31m4k1xfrVWn6o+IGHlj9Eg7OBiXETuW/OfQEPpXtjbc1a/vDjHyhuKSbNksZDhz3EyTknD+apSwaA5vZmvi7+mmfXPku7t52Tck7i+snXkxrR5blaU7OGP6/4M2WtZaRb0rl/7v38Y90/WFm9kihjFHfPuptjMo7BoBUF0pram3hn2zs8v/553D43p406jasmXXXA3rDUiNSAeUkkI4VV1av4/Q+/p7ytnLSING6Zdgsvb3yZDXUbSAxL5JJxl/Dhjg+5ZvI1vLf9PRaWLSTaGM09s+9hfvr8XuWqq23VvLzxZd7e9jYocMnYS7io4CJiw2L3uV+o4nR7MXYLx7K7pSdEIgkVZDjWIUJJSwnXf3e9X4mqqKWImxbdRLWt2t9nSfkSXtv6Gh7Vg8fn4e3tbzMreRYfFX7E5vrNANQ767l50c1sqNvALYtv8VdTX1+3noeWP0Sra9/KVlVtVdz43Y0UtxQDUN5Wzg3f3kB5a/kgnLVkIFlXu46/r/o7Tq8TFZXPdn3Ghzs/9G/fXL+Ze364h7LWMgDSrel+AwSEwXHHkjvY1rDNv8+a6jU8ueZJ2r3t+FQfH+78kC+KvhjS85JIhory1o77XVu5//0Dyx5gSsIUQIiFPLn6SY7KOIpbl9xKXkweIAQeblt8G9sbt/d6jMXli3l96+v++/hLG19i+e7lg3dSw4zd5cWg7fKEOFy+YZ6RRCLpK9IIOUSobKvE5rYFtNU56qhsqwRESMxnRZ8F7Wf32NnasDWgzat6KW0pxacG3uzX1q6l1l6773nYKv2GSyet7tYhl3GV9J81NWuC2j4r+oxmZ4c6VmsFje2N/m3j48b7DZBOVFRKWruUfrrHvnfySeEntLnaBmraEsmIobKtMkilsKm9CZPO5H/fGXrl8Xnwql1KT3t+dnrCp/r4dNenQe0LSxYeyLRHNHuGYzndUh1LIgkVpBFyiBBljELZo2CoXqP3q65oFA0T4yYG7WfWmokxxQS199QWZ47DYrDscx6Rhsgg5ReNoulRKUsyssi0BseTF8QUYNabAYgyRaFTuv63dY46UsJTgvbpfu30pGQ1LnbcAeeFSCQjkShTVJCCnE7RoVECv4o7ldz2VM7q6b7bHY2iYVL8pKD2cbF9K3AYijjdPr8RYtBpZZ0QiSSEkEbIIUJ2ZHaQctEdM+4IeLA8ddSpJJi7KlUnhyfT6GzkkrGXBHxJnpN3DmNix3BG7hn+Nq2i5d7Z95IQtu9K15mRmUFqMDdOuVEmDocA0xOnMzZmrP99hD6CX4//tT+/Y2zMWK6adJV/+5dFX3LdlOsCDJMTsk4IkA6dlTyLvKg8/3urwcpFYy+ScrqSg5JsazY3TbspoO2KSVfwTck3/vdn553NjxU/ct7o81hZ1eVJPDn7ZEZH9y7ccdqo04g3dykdplnSmJ8x/8AnP0Jxur3otdITIpGEIoqqqsM9h34zffp0deXKlb13DFFaXC1UtlUSpgvDordQba8m0hgZIDu6P9jddrY3bqfGXkNGRAYqKm2uNtIi0vyqRRWtFWxv3I5G0ZAQlkBlWyVWgxWDzkC1rZoYUwx50XlEGiNpbm9me+N2Gp2NZFgzyI3KDfJy9ITT42R743Z223aTaknFordg99hJCk8i2hQNgMvroqy1DFVVSYtICwhXGGKU3rsIQvG6rLXXUueoI9oUTVJ4Uq/9K9oqutSxYkaTHx0oRFBvq6e4tZiG9gaijdFkRmTS2N5ISUsJkcZI8qLzMGlNlLeVo9PoSItIo8HRwPbG7bh9bkZFjhoQBR+3101Zaxle1UtaRBpmnfmAxxxh9Pm6hNC8NkMNVVUpbyvH5rZh1pqxe+yYdWbcXjdajZZ2b7uox6QPY0fjDirbKokwRKBFi6qoNLU3EWGIABXMejOjIkdRba+mtKWUSGMk+dH5RJmiejy23W2noq3C/5mqtlWzo3EH4fpwwvRhmHVm0ixpQ+VhHNJ75l+/2kpNSztnTU2jusXJX77cyrK7jjmgMSUHJf26Z0qGhkFVx1IUJR14BUgCfMALqqo+sUcfBXgCOAmwA5eqqrp6MOc1kilsKuTeH+9lfd16zDozFxZcyM+7f6a4pZgH5j7AkWlH7ne9gzB9GJMTJtPa3sqnuz7l8dWPY/fYyYvK4w+z/8CUxClBqkIFsd2KW+1RRiTSGMmMpBn9nodJZ2Ji/EQKYgr4tuxbHlz2IC2uFrIjs3nk8EeIC4vjn+v/yVvb30JVVU7JOYXrp1zfo7yrZP9ZVb2KO5bcQbW9mlhTLH88/I/MTZmL+EgGU9FawetbXxdJrz4Pc5LncNO0mxgb2+UdKWwp5K4f7qLGXkOcOY4/H/5nZqfM9qumlbWU8eCqB1lYuhCdouOScZdw8diLOSLtiAE7r3p7Pf/a9C/+u+W/eFUvx2cdz++m/k6qZUkGDafHyZdFX/LnFX/231NPzz2d78u+55TcU/jbyr/R1N5EmiWNR+Y9wqT4SUyMDw5/3ZMoU1SvsuVlrWU89vNjfFv2LTpFx2XjL+OigosYGzuW59c/z3s73kNVVc7IPYNrJl/Tp8WGUKJ7OJb0hEgkocVgh2N5gFtUVS0AZgPXKooydo8+JwJ5Ha8rgH8M8pxGLE6Pk6fWPMX6uvUAODwOXtzwIvPS5tHU3sQti2+hqLnogI+zoW4Df1rxJ+weOwA7mnbwt5V/o95Rf8Bj94fC5kJuX3K7P1GzqLmIB5c/yNLKpbyx7Q18qg8VlU92fcK3Zd8O6dwOdqraqrh50c1U24U6Wr2znt8t+h0lLXtPfF1Ts4ZXNr+CxyckMJdVLePDnR/i8wmBgorWCn636HfU2GsAkRNy06KbKG0p9Y/x6a5PWVgqkmQ9qlDuWcaLKkgAAHnOSURBVF0zsGsOP1f/zH82/8ef1PtV8Vd8VfzVgB5DIunO9sbt/GHpHwLuqd+UfMPx2cfzwLIHaGpvAoQa4K2Lb6XWsW8Bj76iqiof7fzIf3/0qB5e3PAia2rXsLRyKe9sf8d/H/1g5wcsKV8yIMcdSdhdHr86lkGnod0j1bEkklBhUI0QVVWrOr0aqqq2AluAPZcjTwdeUQXLgShFUQ7JJe8GZwOLyxYHtXdXS+mUdjwQOiVUu7Oubh27bbsPeOz+UN5aHqSw5fF5evyi/KLoC7w+ucI1UFTbq4NUyhweB1W2qr3us6FuQ1Db9xXf+42O3bbdQco/NrfNP2abq40vi78MGuPn3T/3e/77YlnlsqC2L4q/wOnpX8E3iaSvlLaWBrWtq12HT/X5jfZOdtt2B0ijHwitrtYeDexV1atYtXtVUPvBaIx3V8cy6DS0u32EYpi5RHIoMmSJ6YqiZAFTgJ/22JQKdH8qLifYUEFRlCsURVmpKMrK2tqBWUUaaVj0lqAYewhUSIk1H3jBqZ7GSLOk+ZWyhoqe5uH2uhkfNz6ofVritP0OQxtMQvW6jDRGBinvaBSNPyenJ3pSxxodPdp/3USZooJygrSK1q/oY9KZelTu6emaPxACQgg7mJIwxZ9Af6gQqtdmKBJnigtqS4tI6/Gas+gtRBoG5l5r1pt7VDXMi8ojJypYeW5a4rQBOe6BMNDXpdPt8xcr1Gk0KAq4vdIIkUhCgSExQhRFsQDvATepqtqy5+Yedgm6g6iq+oKqqtNVVZ0eHx/fwy6hj9Vo5Y6ZdwQk0R6eejg7m3YCcM2kaxgVOeqAjzM2diyn5Jzif2/QGLhtxm2kRaQd8Nj9IS8qj0vHXep/r9Po+N303zE/fT6jorrOM9WSymmjThvSufWVUL0uM62Z/H727wNUz26ZdkuPkrmdTE+czoTYCf730cZoLiq4yC/Rm2nN5O5Zd/uloBUU7phxB1nWLED8f39V8CtiTV3G58S4icxKnjWQp8bclLkBKl6JYYmcm39ukAzqwU6oXpuhyJiYMZyde7b/vVFr5FdjfsVnuz7j1+N/7W/XKlrum3Mf6db0ATmuXqPn4nEXB3ymJsVPYkbSDI7OOJpsa5fqYHpEOidknTAgxz0QBvq6dLq96HVdn22jXoND5oVIJCHBoKtjKYqiBz4FvlJV9e89bH8eWKSq6hsd77cBR6mqute4kINd6aW4uZjilmLC9eFYDVYq2ipIDhcRavXOepLDkwMe0nujxl7DbttuIo2R6BU9dc46IgwRlLeW0+BsIMuaxYS4CWg0A/+Q1tLeQllrGUatkUxrJnptoPRqm6uNwuZCGhwNpEekkx2ZjVajpcZWw87mnfhUH6OiRvnPfxg4aNWx3F432xu3U22vJt4cL5Sr9lAh2922m13Nu9ApOvKi82hzt1HaWkq7t530iHTyovMC+ru8LgqbCqmyVZEUnkROZE7QmBVtFexq2oVeoyc3Kpe4sOBV5AOl1l5LYVMhHp+HnKicA1aWG4FIdawRRkt7C4XNhdhcNsx6MzaXjShjFG3uNlDA6XYSa45Fp9ERY47Zr3tao7ORirYKwnRhpFvT/VLWFW0VFDYVYtQaGRU1ijiz+ExV26opbCpERWVU1KihSkof0nvmL59fxvwxCUxMiwLg2tdX8+WNR5BgHTZFRcnIRKpjjUAGWx1LAV4CtvRkgHTwMXCdoihvArOA5n0ZIIcCWZFZZEVm+d9nW7P5ovgLHlnxCG3uNmJNsUIpK/3IXsdaW7OWWxffSrW9GrPOzOXjL+fzos9pdDby6LxHOT339EE7j6KmIn7/4+9ZX7ceraLlknGXcOm4SwNCfiwGS48hOgnhCSSE77vmiOTAWFW9ituX3E5jeyMR+ggePvxhjko/yu8x2FC7gcdXP86K3StQUDg552SmJkzl4Z8exqf6mJY4jfvn3B9wrRq0BgpiC3oMieok1ZJKqmVwlariw+KJD5Or/5Khw2q0UhBTwGe7PuORFY/g9DpJDk/m4rEX89qW17hz5p3c9N1N1DnriDHF8Jcj/sLslNl9Hn9H4w7uWHIHO5p2oNPouHbytfxy9C+JMETs9TOVGJ5IYnjiQJ7miKO9mzoWiLwQp1smp0skocBgxyccBlwEzFcUZW3H6yRFUa5SFKWzqtnnwC5gJ/AicM0gzynk2NywmfuX3S9W1BDekPuW3kdhU+E+96t31HPX93f5FZAcHgfPrnuWk3NOprG9kVsW30JFa8WgzNnj8/DfLf/1K315VS8vb3y5x+RmydBT0VrBrUtupbG9EYBWdyu3L7k9QB3r65KvWbF7BQAqKp/u+pQae42/+OCq6lV+9R2JRAI7m3Zy/7L7/WIiVbYq3t3xLpPiJ/HIikf8UtQNzgZuW3IblW2VfRq3UzlxR9MOQNxfn1j9BJvrNw/OiYQQTo/Xr44FQqZXhmNJJKHBYKtj/aCqqqKq6kRVVSd3vD5XVfU5VVWf6+ijqqp6raqqo1RVnaCqqowZ2IPKtsoghZV6Z/0+lYwAah21QWpaPtXnVwlqcbX4lY0Gmpb2FhaVLwpq39qwdVCOJ+kftY5amtubA9rave1+hbQGRwPLq5YH7bereVfAiuu3Zd/S2t46uJOVSEKEntQLC5sKSY1IpbytPMA719Te1Of7b2N7Iz9W/Bh8vNYDV0sMdZzd1LGg0xMijRCJJBQ4tDI1Q5SEsAR/sm8n4frwHhVZuhNtjA5IWOykM0bfrDPvUw3pQAjXh/cYZtU9UVIyfEQbo4OqiGsVrV+xLNIQybjYcUH7pUek+z1rANMSphFmCBvcyUokIUKCOTiENDk8mXpHPbGmWNpcbf72/tx/rQZrj6qBiWEHd6hVX2j3+AI9IVrpCZFIQgVphIQABbEFXD/len+svk6j486ZdzImdsw+90sMT+Shwx4KkGI9f8z5LClfgk7Rcf/c+3uUXR0IjDojV0y8wp8gCTA/fX6fqgRLBp8MawYPzH3AH1qlUTTcPetuv5Go1Wo5bdRppFm6FNMmxk8kzhznL8iWFJbExeMu9ifHSiSHOvnR+fx2wm/97806MxeNvYhvS7/l1um38nnR5wDoFB0Pzn2QjIiMPo0brg/n1um3YjVY/W1n5J7B2Lg9a/8eevTkCZFGiEQSGgxqYrpkYAjXh3Pe6POYkjCFGnsNGREZ6L0uVhd/R1JkBi0+N+3edhLCEqh11PprM+y27yYpPImXj3+ZstYy4sxxWPQWZiXNIik8CZPWxJqaNaRaUv3Jiy3tLZS0lqCgkGXNwmKw9GmOTo+T4pZinB4nCeYEGtobUFD49/H/ptJW6VdtGepaJJKeURSFYzOPJdWSSmVbJQlhCYyPHR+gXjY1cSqPH/04xc3FaDVaciJzsBgsZFozafe2kxuVS2J4Imtr1tLU3kRGRAY5UTmsqV5DraOWeHM8E2InUN9eT0VbBRGGCLKsWdjstZQ27kSnNZAZnUd42IHXvpFIhgubo4ltjdto89iJMscyO3k2c5Ln4PF50Gl0NLY38vQxT5MXlUdudC519jqSLElkWbPY2rCVans1UcYoDIqBMEMYGdYMamw1VNoqiTRGkmnNpMHZgFf18vyxz9PkbCLCEEFOVA5ur5u1NWsxao1kRWYFeTcPBdo9wYnp7dIIkUhCAmmEhAgRxgimJ02nra2W17e+yrObX8GrekkMS+SScZfwt5V/Izcql2MyjuHZdc9yWMphpFhSeHf7u5yZeyZe1UuWNYsXNryAw+MgXB/O1ZOu5uWNL6NVtDwx/wmiDFE8uPxBfy7AUWlHcdfMu0iJ2Le8ab2jnufXP8+bW99ERSXbms3puafz+OrHmZsylz/M/sOQ1yCR9M6yymXctuQ2bG4bJq2Jhw57iGMzj/UXhSxpKeHh5Q+ztnYtADdPu5mi5iI+2PkBIGojXDnxSm5bfBse1cPpWaczK20WDy9/GLvHjlln5u6Zd/NV0Vf8UPUDWkXLNZOupqKljPd3fQTAqRkLuGnSdSTEHHj9G4lkqKluLuXV7W/x6pb/4lN9JIUncfHYi/m+7HuOzDiSv638G26fmyhjFP931P8xPWk6iNqdfFn0Jfcvux+b24ZZZ+bW6beysGQh5xecz/1L76fB2YBRa+RvR/6Nh5Y/RLW9Gq2i5epJV3NBwQVU26u5ffHtbG/aDsAv8n/B1ZOvDvA+HwrsGY5l0Ep1LIkkVJDhWCHG1roNPLXpX3hVsdJTba/ms12fcWTakWxr3EZpaynZ1mx+rPyRSGMkJp2J93e+z7y0eTy77lkcHgcANreN59c9z2mjTqPWUctDSx9iU/2mgGTkReWLWFKxpNc5bazbyBtb30DtqDFZ1FLE+tr1jIsdx9LKpXxb+u0g/CUkB0J5azl3LLkDm9sGgNPr5O4f7qa4pdjf55PCT/wGiE7R4fQ4/QYICJGBhSULyYwUIX2n5Z/GQ8sf8odrOTwO/vjTHzk191RAKKQ9tfZpUiO7QlA+KV3IymqpRSEJTTY1buU/m1/xK8Tttu3mq+KvWJC1gEdWPILb5wZEEvpdP9xFrV1UCN9av5UHlj3g//w5PA7+suIvXFBwAY/+/CgNzgZAFN58bv1z/jwsr+rl6bVPs7l+M69sesVvgAC8vf1t1teuH7JzHwl4vD5UVUWr6cqZ1MucEIkkZJBGSIhRYQuWdNxUv4nc6FwANtRtID86H4BdTV1KRs3tzf4vxE5a3a0YtAYAtjRuod5RHzT20sqlvc6pUzayO+tq1zE6ZjQAS8p7N2QkQ0utvZZWd6Cqldvn7pJzdjtYVLbIvy3aFE1lD9feurp1/uutwdngN3I7cXqdQW3t3vbAMeo37u9pSCTDSpWtOqhtQ92GIDVDEAZKvVPcY6vt1X7J9U5cPhfNruYAxau86Dw21gV/PiraKvixMlgta1vDtn6fQyjj9Pgw6jSIkmQCqY4lkYQO0ggJMZJ7qHg7JmYMxc3FAIyNHcvO5p2AKHrYKeMbaYz0JyF3EqYLw+sTN+u8qLwelVpmJc/qdU6jIoNDacbFjfPXMTks9bBex5AMLbHmWMJ0gapWOkVHQphQ9zHpTByW0vV/a2xv7LHC87iYrv9ztCkakzawSrFBYyBMH3ic7kIJAONj9l7YUCIZySSGBathjY0d26NYQ0JYAjEmEYsVb44Pyt/QaXREGiJJCe8Kf93VtIsxMcECJMnhycxMmhnUnhed1+9zCGWcbi96XeBjjF6rSE+IRBIiSCMkxBgTO57L88/zS/ZGG6M5fdTpfFv6LZnWTHKjcilsKmRawjScHic2t42Tsk/ip6qfuGLiFeg0whAxaU1cOfFKPi78mEhjJPfOuZdxseOYGNelXjUjcQbz0ub1OqcJcRM4fVRX5fXk8GRmJM1gXe06JsdP5piMYwb4ryA5UDKsGfzp8D/5jQadJlAtTVEUzsg7w+/l8Pg8GLQGjss8zj9GpjWT47KOY0ej8IR9tesr7px5JwaN8K7pNXrumHkHn+z8RIyJwuXjfk1pc1dBxPnJhzEjacbgn7BEMgiMixnNL/J/4X8fa4rl5OyT+ab4G26aehNaReRXhevD+eNhf/Qb+WNixvD7Wb/3G+R6jZ5bp93KO1vf4dYZtxKhjwCEF/mqSVf5jRcFhV+P+zUFsQVcNv4y0iPS/cc+JeeUHmXRD2baPT6MWm1Am17mhEgkIYOiqupwz6HfTJ8+XV25cuTEkdc6ailpLkGv1ZNtzcZqtPa+0wHgdDRR1LCNlvZmEq0ZtOHB6XGSGJZIjaMmQB0rXBeOTtFR0lpCUlgSRp2RxvZG4kxxeFUvTe1NpFnSSI0QYVuNLeUUNe5AoyhkReURZU3tZTYCm8vGrpZd/nk0OBv8SepRpqhB/GsMOkrvXQQj7brsDY/Pw5b6LVTZqkgIS6AgpgCjLtBLUe+op7ilGJ2iIysyC42ioai5CJfXRaY1E5PWxNbGrTQ5m8iwZpBpyWBj4yaqbdUkhiUwNqqARncz5W3lWA1WsiOzaWurpqRpJzqtnuzofKyWYO+epFf6fF1C6F2bI5FWVyvFzcW0e9vJtGb6Cw822WrZ3rSdVreNaHMczc4mUs1xZLe7KDJoafC1kxKeQoY1UI63++cvxhSDXtETZggjKzKL3bbdVLRVEG2MJjsymzpHHeWt5VgMFnIic/y1nmrsNZS0lGDUGv3qdSOAIbtnFta2cfFLK3js3C7j6+O1FVhMeu45WXpYJQH0654pGRqkOtYBsrNpJzd/dzNFLUUALMhYwB0z7yCph7CpgcJkjqIgtecwqXRr18pY9y+90bGjex+4fifR719JdEXHl0Lm4XD6MxCT1euu4YZwJsRN6PHYkpHJ4rLF3PH9HbR724UnZM79nJRzUkAoSaw51l/AsJM9a734PRk+H2z5iOkfXAmedtAa4PRnCBt/tt/IBTBFZRIXNTj1aSSSwaDGXsNjPz/GF8VfAJARkcHjRz9OXnQeUeHxzAzvqITe3gYrnodvHwbVR74pCs5/HZKD74c6jY4J8ROYED8haFt6RHqAlyPFkkKKJVilMCEswe9dORTZs0YIgEGnxeEKzsmRSCQjjz6HYymKcpaiKDsURWlWFKVFUZRWRVFaBnNyIx2vz8tbW9/yGyAAC0sXsqp61TDO6gDY9BFUdFuVKvkBdnw1fPORDBqlLaXc/cPd/iRxj8/D/Uvv9+cW7RcNhfDh1cIAAfC64OProH7ngU9YIhlG1tSs8RsgAKWtpbyy+ZUgsQ+qN8H/HoQOtSycTfDhNdBWO3STPYRwun09GCFSHUsiCRX6kxPyKHCaqqqRqqpaVVWNUFV1cOOORjg2j41lVcuC2jfXbx6G2RwgPh/s/Dq4fdfioZ+LZNCpd9T7pXQ78ageah0H8LDUVgPuQCUsPO3QFqwgJJGEEj2pTq2oWoHNZQtsbKkI3rmxGOzByoOSA6fd7cWgDYyyMUojRCIJGfpjhFSrqrpl0GYSglj0FualBidudw9LChk0Gsg/Mbh91Pyhn4tk0IkPi/cnv3ai1+hJDEvc/0EjksAQHtimN4PM+ZCEOAWxwfkFR6QeEZyDEZke1I/YPOgM15IMKKJQYWBiuixWKJGEDr0aIR1hWGcBKxVFeUtRlPM72zraD1k0ioZzR5/LuNhx/rbTR53O1MSpwzirA2Ds6ZB9dNf7/BMh77i995eELGkRaTwy7xEsevEQZdaZ+dPhfyLLmrX/g8bkwFn/BGOHcWMIhzNfgNjcA5+wRDKMTImfwjl55/jfj4kew/kF5/vVBv0kjoMT/wLajrwqSwKc8SyEB+ZVSQYGIdEb6Akx6DQ4XNITIpGEAn1JTD+12+92oPtTqQq8P6AzCjGyI7N5bsFzlLSUYNAayLRmBtVFGFSaSqF6owh7iS+AhD005X0+qN8h+oXHQdxoMOxlfjHZ8Iv/iBh+RREPj6a+Rdw1tzdT2FSI0+sky5rVYxKlZGQxL20eb5/6NjX2GuJMcWRYMwKKfgHQUgV120Cjh/j8fa/oKgru/GMp+vUnVLdVkRCeRE7cePSaXtY6bPVQu1XkkMTlgylSvHc0CVEEacRIhpm4sDhun3g1v8g4FpfHSUZkNtGmGCj9CVxtEDsKorPEvXX65ZB9pEhSV73gbIbabcIj0ttnAVBVleKWYipaK4g2RZMTlRNUU0QicHq8GLTBOSGyWKFEEhr0aoSoqnoZgKIoh6mqGlCiVVEUWYUOiDJFDY8MbfUm+OxWKO2oah6ZBme/BBmzu/oU/g/euqArWXj+H2DW1WAMDx4PwBwJadP6NY0aew1//unPLCxdCAit/H8s+EePIQySkcWeKjwB1GyFN86Dxg7hhYw5cOZz4mGrB7w+L18WfckffvwDXtWLVtFy75x7OW3UacErxp00lsJH10FxR+7RpPPBaBUKQwAGC1zwDmTO3f+TlEgOlOYKzJ/eRMGOjry5iBQ49gF4/7fivTkaLnwfUqcKL0hkBvz0D/j2IbFdZ4Jf/hfyju31UMurlnPDtzfg9DoBuGriVVwy7pKRIr87onC6feilESKRhCz9yQl5qo9tkqGieGmXAQLQXA4//xPcHQZHc0WgWhGIL8XagU3tWV+73m+AANQ763lh/Qu0dz+uJLRQVVjzSpcBAlC6DHYt2usupa2l3L/0fryqeADwql4eWv7QvhW3Sn7oMkBArCh3GiAgVpk/uVF4SySS4aJ0OezoJtzRWgmbPoCUjtBbRyN8c5/wfgDUbu4yQAA8TnEvbqnc52Fq7bX84cc/+A0QgOfWP8fOJqkw1xM9SfTKxHSJJHToS07IHEVRbgHiFUW5udvrfkDby+6SwaR2U3Bb5WpwNorfHQ1g60HtqLVqQKdR2lIa1LamZg2trtYBPY5kCPE4oOj74PbyvctPNzgacPlcgcP4PNQ792FAVK0LfO92Bvep2y6kTiWS4aKnhZvqjRDXLVSwcpUIvQJo7UERzlYL9oZ9HqapvYlqe/C+Nfaa/sz2kMHp9qHT7JETotXQ7pGJ6RJJKNAXT4gBsCBCtyK6vVqAc/axn2SwSZke3DZqPoR3FK+yJAaHzigaGOBCcXnReUFtR6YdSaQpckCPIxlC9GFQcGpwe3awGlwnCeEJ/kT3Tsw6M0lh+1DHypgT+L6nfKW0WVJdSDK8pEwJbsuYDZVru97nLoCwjgT0qHSRV9ed6GyRqL4P4sxx5ETmBLWnWlJ76C1xur0yHEsiCWF6NUJUVV2squoDwGxVVR/o9vq7qqo7hmCOkr2ROQemXCQMC4D02TD5gq7kR0sCnPUiWDuSxA3h/9/eeYe3WV1//HMl2ZL3XrEd29k7ZJIBSdh7QxltWaVAWd39ldJCoS2lLR20lFJaKKOUvTdhZADZe2/HdmzHe0uyZN3fH1e2LFtesWRJzv08jx7rvXrHkXV19Z57z/keuPgfkDbB9/mOkampU7lp6k0YhVoYm5I6heumXOdVeVsThky9Akafrp4LAbOuh/yTetw9Ny6Xhxc/TKI5EYD4yHgeXvQwI+O7V4vuYOR8mPNtzw1bfQmc9VswmdV28ig47+F+CyRoNAEhdy7Mv7PTWDsfJlwANQfVdsYUWHI3RFjUdtpEuPhxj2R1/Ai49Ik+nZAkSxK/XvhrMmOU424xWnhgwQM+J3o0YHW0EdEtHMuoJXo1mjBBSCl730GId1AqWD6RUl7Yy7FPAecDFVLKKT5eXwK8BbQHnr8upXygL6Nnz54t169f39duoU/jUajYCS4npI2HRPfNWtU+pVBljof0iRCd7H2ctU4dZ6ujKmUUBxqLsLfZGZ0wmuy0Se5zHIDqvThjMjgoHJQ0FpMancZocxoxtYdU4mRrozpXymilSiSEugms2K2ep0+C+CylsFW5W+UHxKQpJ6bLTaGjzcHhxsPYnXZy4nJIMA+bVRDR9y6KYPfL8up97K/di8FgYEzSONKTRvd+gLNVfa71xSrRNn2CquvRGXujutEymCB5FNUtFeyv2YO9zcaoxLHkxGarvthSoxyGmHRK6/ZT3VJFclQK2YljoO6QCqmKSoHMaeByQNVuMEaqmzVLgqq23uZQ54iMUde0NagZ5T5u3I5T+t0vIfh9M6xoKIWKXSovKn0iJLhXIY7uVMUInTZVD8TVpkKsHM2qH0clQ9kWmoSL/VExWA0mhJS02GrJTchjVMokjIb+RTBXtlRS3lxOfGS8b9W60GbIxsx739qOlHDu1KyOtjaX5JtPruHgb88Nt/+bJrDozhCC9Eei92H330uBTOC/7u2rgcI+jn0aeBR4tpd9Vkopz++HHcOLmkPwyg1Qtkltx2XB119VN33PXwbtlXgnX6p059tvxJqr4OOfw5YXOHL5v/jpqvvYXKMqtKdYUnh80cNMcLrgv5dCbCYrzvwpP1zzG5zSCcBN467kW8Z0Yre+BDvfUuc0meGal1VRuReuVBV+Qcn5XvW8uiF86evqJhFg3u2w5KdejkiEMYIxiVpKNVjsL9/E7St/QmlLOQBj4wv480kPkpfWzfdXuFyw/VV46zZ1swVw5m/UqkSE2bOfOQ6ypgNQWr2bu7+6n4012wFIMifxzxk/YuIL31T7pk6AWdcx4uOfMUJKFdJ14d/grdvVjRvAlMshYyp8ep/azp4Flz+l6it0JlXP/GqCQNU+ePEa5TSDCqG65kXlEH/0MyhZp9pn36jkq/d+oLbNcXDuH2nY8RqPZeWxx15Fblwub+x/AwCTMPHHJX/k1JH9K/6aFp1GWrQOQewLa2sbCVHeK+5Gg8BkFNidLiwROm1Vowll+huOtRyYIaW8Ukr5jvtxDdBzbIY6dgXQeybe8crBZR4HBFSy+Lp/w+p/eBwQgB2veyfvlm2FLS+AJZF1rsYOBwSUKtWzu5/Hse8TsDdSdspPuG/TIx0OCMC/977EgdR8jwMCSj1r2UOw9SWPAwKqPsSut+GTez0OCMDqv6ukTE3I8NbBdzscEIB9DYdYUbKi5wNqDsC73/c4IABLfwHVe3s8ZMPRjR0OCECtvZaniz7Eke2WdJ50geor7eecfDF89muPAwLK8YntdHN1ZAMc6sVOjWYo2fm2xwEBtfq762Mo3eRxQEBNGrU7IKAmj9Y+zt4p5/N80YfMy5rX4YAAOKWT+766j7Im/4qCHO/4UseC9pAsnRei0YQ6A5HoTRNCdGTMCSEKAH9M1cwXQmwRQnwghJjc005CiJuFEOuFEOsrK30oPoUbZVu7t5WsVaFZXWny3FzS7FZOSR7Nfh+qVFvr9mGNVqFQ9aYI6ux13fapttd2v4YwKAnWrhSvA1+FspqGwWfgB0KhXzodNjbW7u7Wvq12T88HtdR4OwcA0qVW2nrgoA+p3a2Nh2hJaR8WpLezGj/CW+K3nXYFoXbKtUMbCEKhb4YdJWu6t7XWeXI/AAxGcFi771e5hyqhchG6qsSBUr5qaG3wk6Hhiz/7pa9ihQDmCC3Tq9GEAwNxQr4PLBNCLBNCLAM+B743yOtvBPKklNNRNUfe7GlHKeUTUsrZUsrZaWnDYJl61OLubZMv9airdCa5U2x/kvuGr3wLM5O7FwM8e8TJxLWom7z05loK4ryVsIzCSLYvtaLIWJh8Sff2CeeC6LKkLYSqZK0JiX5pirBw9ojui5KLMuf52NtN/AiISfVui4hWuUI9MD1tare2s1JnEl/sjul22lXRtnbKt6mE3q7EZnhv95Lsrjl2QqFvhh0TfEQGJ2R7q2O52jwJ550pWESuCwSCSENkh1BHx8sJBaRH6/wmf/ZLm8PVLTEdwGIyYm3VTohGE+r02wmRUn4IjAW+636Ml1J+NJiLSykbpJRN7ufvAxFCiNQ+Dhse5C2ABXephF+ASRfD1Mth/u2QM0e1RUTDuQ9D5nTPcZlT4YJHwGRmRk0J3x5/dUc16lNGLOSiUecjpl4GIxeQ/PF9PDjj++THqhvL+Mh4fj/3Z4ze9Cqc8nMVxwxK2eW0e2HCeUpdSwi1MjL7JhhzBpz/J5UfAiqJ+NInVSKmJmQ4PfdULhh5OgKBURi5ZvTFnJh1Ys8HJObC156DhBy1HZuuKjp3rGp054T0mdw68Zsd/W1x1gIuzT0N0eKuA1K8TqmvtauxlW+DJT9T/QtUfzv7d1DnXsEzmOCk7yuVN40mFBhzOsy6UY1/Qij1wXFnqTym+XeqauigVgxPv98j5JA7H2bewLi1z/LQlFv4pPAT7phxB/GRKm8uPz6fB096kCRLUg8X1hwLVkcPKyEmAy3aCdFoQp7+qGOdKqX8TAhxqa/XpZSv93F8PvBuD+pYmcBRKaUUQswFXkWtjPRqVNgpvVgboGI7NFWoGh3pk1Tyr9MBtQdVCFZSgadGgrVe3ahFxkByQXe9eSlV7oa9CUf8CEqaSmhztWE0RlBYuw+jMDA2cQxZLiAihhqTkaNNpcSbk8g2J0LTUZWE7mhRscztakROq1InaqpQP8JRKSqcpt0Oe6NyjOyNUFeoFGLSJ/qeFRw+hI06ls3eQEntPoQwMjJpHBG+am50pbFcfd7RKbjiszhQd4DC+kLiIuMYlzyO5JY6pRRkMEHGZJwYKa7fj9PlYERsDjEx6Uody96oZoxjsqB8s1JZS8hWSe2NZVBXopyQjCmqiGZtoTpn6hiI1zUQjgGtjjVYqvcrJUBTJKRPgQS38+y0QU0hINW4XFuoHOqYVKXoJozQUq1UseLc6oFCqCKxselgMFMSFYNVGDAZTNjabGREZ5AclezTDLvTzr66fZQ2lZIWlcbYpLHERsb63DdMGLIx8/y/ruRrs3MZmxHn1f7AOzt44OIpzMn3/T/XHJdodawQpD/qWIuBzwAflcuQQI9OiBDiBWAJkCqEKAHuAyIApJSPo4odfkcI4QSswFV9OSBhh70RvngYvnxEbQsBF/0DTrgaTBFKmrcrUQkQ1T30pQMhlFOA+mcWxKSwp3QNN33+g47q1CNjcnh04a8pSJlCMpDcOcwmrlM4TO1heOV6VWkdlCzwKT9Tzz99QDkqAHkL1Sz3zrdUAnM7Z/1WKSqZdE2QYGMxxzMmc9bADorLVA9gbelqbvv0NhwulddxWs4p/NxmJHXdU2rfU36Oafc7FLQLJVgS1Erd699W22PPgZyZ8PlvPOdf9BOV6LvzTbU96SKIiIEt/1PbaRPhqv/1ugKj0fid0s3w3MVgdefHZUxRK4HJBWCyKLlqUAnpr39bqWYBzL9D5e4Vr1XbkTFwzu/h7TtVTpUxEr7+Gjk5M/tlhku6eP/Q+9z71b0dbTdPu5lvTfkW0RH9mEQ4zrE5Xb4T0yN0OJZGEw70Rx3rPvffG3w8buzj2KullFlSyggpZY6U8kkp5eNuBwQp5aNSyslSyulSynlSyq/887ZCiMrdHgcE1CrGBz9WEr1+Qra18fqBdzocEICi5hJWlvlINO9K0SqPAwJgb1D1S3a86XFAAA5/CcVr4NP7vY9f+guo1jUrw506Wx2/WfObDgcE4NOSz9mVppxdTBY1Q9xZqc1WD9te9uR9TL8Clv/O+8QrH4ZJnUoJ7Xyrw4EGoHIXHFru53ej0fSC0wGrHvU4IKDU/nyptB1a4XFAhAHMsR4HBJSS4ab/wqhT1HZbqxrfW/onClncUMyDax70anti6xMcrD/YwxGazvSsjqXDsTSacKDfOSFCiANCiOeFELcKISYF0qhhRXN19zZ7I9jq/HYJh7OZbQ3df7R21R/o++AaXz920rdUa8MRT0x0Oy6nCq/RhDXNjmYONxzu1l7TLu9sSYDmiu4HVh9QYXmgnNau6m7SBa1N3m1tdu/tyu7KXhpNwHC0eDvT7VT5GPOqOk2wRER3V3YDFdaVmOt9Hntjv0xpaG3A1mbr1l5r86FgqOmG3eHqMSfE6vChNKnRaEKKgahjTQL+CaQADwshDgoh3ujjGE1SvioG2JnkURCf47dLRJrjOW/Eom7tS3pTR2qnPQm+M8ZIGH169/aMKWpGvDPRKSrPRRPWpESlcEruKd3a89sjNpsrfH/OBYs99ROEqbu6myXRW+JZiO59qMCHUpxGEyiiEmDq17q3+1Jpy1/oed7aBNE+dFNGnwKHOy3iT7yguwJcD2TGZpIVk+XVZjFayInz3+/DcMbm9L0SEqlXQjSasGAgTkgb4HD/dQFHAR9ToxovUsfBVS94FIMypqgK0bH+lcw8Lftkrhx1IUZhJNIQyS0Tvs6c9Bl9H5g7V1XKjohWN4gTL1QhBckFMPYstY+7GjAj56n4/SR3OE3yaLXdeRZQE5ZYTBa+O/O7zHM7rvGR8Ty44AHGW62qLoIxUiXdnv5LT1+ZdqVSdWsP29v1LlzyT+Vkg+onlz4Bez9U29HJcPE/odWqQlsiopQq28h+OMsajT+ZdqVbCbC9H94HuT76Yd5COOkHynEWBiVDfdaDStJcCDVGjj9PiTsAjDoVTv05RFi6n8sHaVFp/GnJnxibOBaAzJhM/nrqX8mPz/fTGx3e2B0uzKbuVdF1TohGEx70qY7VsaMQLcA24E/AJ1JKH3FGQ0NYKr00lLvVUzIh2odMY8l6pTJkSVCzx1X71CqKbFPJ47FpkD4V0sb0eAlH9UGOtBxFGIzkCDPG6n0qcTImTYVdRSUrh6LusHIcMqaqGOf6Iyqsps2hrolUP7Ax6UrZyGSGpE6z4E2V0FKlZgX97EyFIGGjjtWNil2qKKbDqhJtu97s25tULHxdkXKSM6fSbDRR3lxOtCmarNgspR5UvgUMEapWgr1Rnddph7SxEBmv+q2tTtWOSZuk+pO1SqmrpU9Ufan+iOprCTnq2LoipY6VmAeGgcyFaNxodaz+4HJBxQ6o3KPGvsxpEO9eeXDaVb9sKlfjY2yGciYMRjVWCqFyO2QbxGSoMS8xFzC4C31K1ceRStlQutT3qF36fADU2eqoslaRYEkgLSrsx9QhGTPbXJIxP3uf5286EdFFQfLl9cUUpMZw12ljj+ncmmGJVscKQfqjjtXO1cBJwG3ATUKIr4AVUspPA2LZcCM+Uz18UfgFvHA1uBxw6i/g1Rshew5MOAeWelRTmHYVnHoPJPooKFe2hYhnLiTf0QJn3K+Oa69enXUC5MyGdf9WxbhcDtj7EZzxa5h4vrp25S61b0Q0XPuWJ9nY4uMHNTbteHA+wpuybfDajZ4494gouPJ/MOZUtd3mgA1Pw8f3eI456fvELPoxoxPdxTFLN8OzF3ri4E/5OWx9UcXAg1sZ6A/w1m1qWwi44FGVjN5eKX3xT1UtkHa1IVBObaq+OdAMAYUr4fnLPGPhyPlw2ZNKPtpkhvpiePmbarVj6S88CeWxGbDgTvj452rbkgiLfgTv/xDO+BW8+z3VbrLAN9+AEdO7XnlAJFoSSbQkDuocxxs2RxuWCEM3BwTAYjLQZNc5IRpNqDOQYoVvSSl/DNwCvA9cD7wbILuOHxx2WPuEUqWaeAGsf0ol9869CZY95L3v1hfVzHVXpIT1/1Gz0ePPVWotbR6VI8o2q1AagN3vQvZs9fyz+9UMYbsDAiq0Zvkf1Oy5JnwpXu2daOuwwhd/hBZ3wmvNAfj0l97HfPFnTyKuq031y3YHJCJK1ZFpd0BAKQNtf1UV3gTVDz/9pbpZa2fF73wn/Go0gcZaBx/e7T0WFq1Ssrugxt6Nz6g8pspd3opWTUeVgqFbvhpbnTouIQf2fQTZbglepw0+/bVaVdQMKVZHm89QLFDhWC3aCdFoQp6BqGO9JoQ4ADwCxADXArr862BxtKhQKIC4ESpUClQIQGeJ3HZa6rq3tTmgfKt6Hp+lwre64rSrmGbwqBO1ObxlKtup2gOtPq6tCR8ajnRvqy1Uzi6ArcH75qwda53629bq7fCa46G50vc54zol1jZXqtW0dqT0rSik0QSa1iZVDLYr7Wp+jmY19saP8D1m1her8Nl2agvVGN3+t52afXq8DALW1jbMEb5vYSwRBhq1E6LRhDwDCcZ+CBgnpTxLSvlrKeVyKWWHtqAQ4gz/m3ccEJ2kknsBClfAuLPVc2tt90KGEVHeNRbaMUXCjG+q54dWwrizuu8TGaNilk1mFYsPqlK1r/OdcA3EpHRv14QP2T6KFk680COnm5irZnU7Y0n05P5ERMEJ3/C81nTUI0jQmTGnqdnldvJO8jjEoNXTNMEjJgOmXNG9PXWc+hudrL4TpZs9q3mdyZ6p8p3ayT8ZjqxXNUGKV3vap12lqqlrhhSrow1LDyshlggjLa3aCdFoQp2BhGOtk1L2Jjfxu15e0/TGxAth1o1Qvg0yp8OE8+CTB+D0BzyhU8mjVCxz3nzf5xh3Niz8viocmDIWJl+sVj5iUlUM8863VdL5WQ/ChmdgxEy46nnImAzn/0XdgBpMMPtG5YRowpvcE9VnbUlUibbtakDtSeBxWapC9Ah3WEnaRLjmJW+ndML5sOAupYwVGQuxWaovWRJUX5nxTbfT7I7JLlikcpb2L1PbGVPg6hchyUcOk0YTaEwRcNL3YMplbqGNVDWGZp3g2WfsGeq70VAGs25QOR4R0bDwuxCdruoimcww81poqVZj9YgZKlzRYFSO+pxvaXGFIGBtbSOyp5UQk5Emm1bH0mhCnX6rY/V5IiE2SSn7oQk7eIal0kvZNpW7YYxQjoetXs1Gt7UqRSKTRYVnVexUzkT2LE+eRztHd6giXAajOocQqkaDOU7NZJvj1WvWWqVsFZXgObb+iLpWfI768da0E77qWAAVe9TnmjIGIqO6v26tV6o/UUnqZqtkLVTuVc5L1nTVhxqOKIc2KR8wKkfX1QYJIyB9kup3jmaIy1YKWEc2uhXYRionx5canGawaHWs/uK0qz5sivIoYwGUb1c5UFFJUF8EliT36qBQ/VlK1Z+Rykmx1ihnPTZDtdnqlQCDvUkJL2ROU+OrZkjGzFUHqvnNezu557zutZP3lDfy+qYS3r7DR+0XzfGKVscKQQaijtUX/vFmjkdK1sMzF3hyQOKy4Lp34MCn8MH/efYbf67KFdn7ESz6CZz8I4hwF0I8slGdo706dUwqXPuOp2aDOdZznujk7jYkZPv/fWmCT/r43l+PSvA4o1tfgjduUTdfoByImdfDu3ep7dgMmH+HUhEC5bRc+7ZH+tdpg+UPw8o/eM6/4C5YcreSMNVogoHJ7BkH2yleq8bL034Bb9+uRBZA1Uxa+bAnV86SAEt+Bh+6x+GIKLjuXTUB9OatavUalPNxzSsqPFEzJNh6SUy3RBho1jkhGk3Io9eQg02bE1b93TsJvbFM1WdYep/3vnve98T6f/lnOOr+AXS5YN2THgcEoLkK9nwQWNs1w4eaQ/DpAx4HBKB0o/fcUdNRNaPc7sQ67bDiYXC4U8Oq9isFrs6s+ptaOdFoQgWnXSnBpY1Xlc7bHZCEXKjc7S3WYatX34N2J8Zhha/+qlTi2h0QUCuDH//cI+ygCTgtvYRjRUUYdcV0jSYM8KcTUujHcx0/uFq9ZU/bsTe4C2J1oV3RqM2hFI4ApFMpWnXF13k1Gl84WpTz25X2G7R2mipU+Eo7tQc9/dTeqMQPOiOlp59qNKGAs1UVJ4xJU2FW7cSk+f4ONJZ5h75W7VPyvl2pL+n+fdEEjJZWJ2ZTDzkhkUa9EqLRhAF9OiFCiEt7e7TvJ6W8tLfzaHogIhpmXde9PalAxeR3JjLWM1OdMgZS3EXljJEw08c5Jl7gX1s1w5fEfJhwoXebMEBchndbxmS1atLOzOsgKlE9T8pXimudic3wrcCm0QQLS5zqtyXrYNQST/vR7ZAzp/v+I+crBa12Zt2gnJKuRfJO+Ianrogm4FgdbZiNvm9hoiOMNLe24a+cV41GExj6sxJyQS+P8wNn2nHEhAtU3HFkjMrluOCvkDkFLnlcqQ8Jg3JIznoQNvwH8hfBRY955FRByfKedq9KQo9OhvP+5Ft2UqPxhTlGVTafcpkSR0gqUEpCrTbl/EanwPl/hrRJasY4IkpVmZ7aSQI1PguufkFJmQoDjFygFLe6SgFrNMFm8iUw9xYVYjj3FtXHzbGQPtGjKmdJgDMeUIqF5jg1Pi/+P6WQlTkVvvacCuEyRsLsm2DerToxfQhpaW0jsoeVEJPRgFEI7E6Xz9c1Gk1o0GdiupTyhqEwZNhhrVMVdqv3qx+qETO6zyq3E5uuVi2yZwIG9eO34031o3j27+DcPyhlK4dNzdTFZnSv4xGbrm4Kp12lbgA7q8BoNAANpXBkAzSWQ9oEpYRWvlkVX0vIgRGz4MK/w8k/VjdcSSPVytvoxUqSt32WN2cWuByqYFtXadKs6XDVC2CrVWFb5rihfpea4UxLjRpXaw561Ndi0/p/vKtNKQiWbYGMSWolRAq1Gh2V7Bk3J1+ipFYS3EUJc2aBy6lW+tpXQCZeALnzVDhiXKZy3jVDRm9OCEB0pJEGmwNLhHYMNZpQZUDqWEKI84DJgKW9TUr5gL+NCnucDljzOCz7radt6tfg3Ie9ZXHbKV4Lz16gEiZBzTqfeCu88xslgXrNyyrkJQqI72W5XwitcqXxTVMFvPEdOLRMbWedoGrOrP6HZ58pl6tZ4IyJnjYhuq9k9ORMt2OJUw+Nxp84bSop/Is/e9pmXgdn/ab/zu7hL+G5S5RDAapa+gnXqNpJ173rcULiR3gf11OY1UAcII1fabY7e3UwYsxGmmxO0vVQpNGELP1OTBdCPA5cCdyJ0sy5AtClkH1RcwBW/MG7bdvLSnmlK21OWPWoxwEBVRSrpUqFVVXsVPVDNJrBcHSHxwEBFb635p/e+2x/Ve2n0YQiVQfgy0e82zY+o+ra9IfWZvj8tx4HBNTqoMulRBUOLvObqZrA02zvOTEdIDrSRINNJ6drNKHMQNSxFkgprwVqpZT3A/OB3MCYFeY4mr1/6Dq3d8XVqgq7daWlBszuVRN7o3/t0xx/dJZvBqVi1VXJCqBV9zVNiOJo7qHPNnVv84XTDo2lPo5vVDlOvpSxNCFLXysh0ZFGGm2OIbRIo9EMlIE4IVb33xYhxAjAAWjZG18kFajExc5EJ0Py6O77RkTD7G91b8+YrKrxGoyqSq9GMxhSx6kbrXYaSpXCWmdi0yFl7NDapdH0l6R81Y87E5fpUQnsi+hkmONjrI3PUbVBRp86aBM1Q0dza8/FCsG9EmLVKyEaTSgzECfkXSFEIvAHYCOqLsiLAbAp/IlOhkv/DZMvVQnlo06Fb7zurWbVmfHnqlj8pAJIHQ/n/AEKv4CMKXDNq5A1bWjt1ww/0sbDN99UilXtij4XParU18xxULAYrnhaJetqNKFIbDpc8YxSpzLHwdgzVb7cQNTXpnwNTvulyrtLGQNn/koVLLziad/yvJqQRa2E9HwLE+VOTNdoNKHLQBLTfy+ltAOvCSHeRSWn+6im50EI8RRKxrdCSjnFx+sCeAQ4F2gBrpdSbhyATcGnzanUWorXqh+1tlaVwxGbAYt+rJImLQlKbagnolOUyoqrTc1W5y1QP7SyTcXof/FnSMxT+5VuVM5JzhylkFWxC4pWQ2sLjDxRJRwbB6Q3oAkHmqvhyDoo3676We5c7+RZKVW/K1qjVs9GLlD9oGi1qvqce6IK75t+lSqqljkFEgvg0n8ptayYNDBFwqGVULJezTDnngi2OnUOkxlGzlMrdBpNsMiYpPqstUbJ6EZGq/aGciheBWVbITEXsmdDfTEc2ajG4rwFKuyqeK2SQf/mm8p5cbYqB7x0Gxz4XBXfNJohbx5k6smfUKalta33xPRII/VW7YRoNKHMQO5WVwEzAdzOiF0IsbG9rQeeBh4Fnu3h9XOAse7HicA/3H/Dh6JV8NxFkDQK5twEH/6f57WUMUpLvqvSSleKV8EzF3rySCwJSqll93uw/CHPfnkLIC4LPvsVLPweTL8a/nOOCiUAdfP5zTehYJE/36Em2DhblSrQl3/xtE04X61ktFcvL14Lz5yvnGCAU+6BtU9Ac6XaFkKps334U2hzePY5+UeQ5g5x2fISvHGz5xop42DcGbDq72rbHA/Xvw9ZXUINNZqhJMICEZ3GVJcLNj8Hn/3a05Y9WzksG59VEzun3Qcf3e0p9ho3Aq57R30/nr0ATv8lfPADj0BIZAxc9x5kzxiyt6UZGM12J1G95YSYTdQ2tw6hRRqNZqD0p2J6phBiFhAlhJghhJjpfiwBons7Vkq5AqjpZZeLgGelYjWQKIQInwIXDhusfFitYJz0PVjZRRGren/fylZOB3z5N+9Edls97P0ANj7tve/hrzwx0V/9Far2eRwQUHas/KOySzN8qNmvPu/O7H4XKveo5y4XrHvC44CYLOCwehwQUDdfm/4LY073tH3xZ1UlGtRqyMf3eF+jeq9yPNqxN8DeD/3znjQaf3F0B6z8k3fbkfWqpgfAuHNUkdfO1bMbS9U+qx9XY2rRGm+FwtZm2PFa4G3XHDNqJaTnW5hYs4naFr0SotGEMv1ZCTkLuB7IATqP9A3AzwZ5/WyguNN2ibutm0yJEOJm4GaAkSNHDvKyfsLlUPUXQCWY2+q779OXQyCd0FTevb25Ut1Mdtu/zf3XBY6W7q83HVV24eNYjd8Zkn7ptPtWBWr//KVLhaO0Y4z03Testd6JvU6r58arrdV3/23vb+00HR2Y7ZqgEZJjZiBw2lRf7kp737XEq+KxXbHVQ0uFcrRtPl7XalkBwV/9srm1d3WsOLOJohofipQajSZk6HMlREr5jJTyFFS+ximdHhdJKV8f5PWFr0v2YMcTUsrZUsrZaWkhUiDKHAcnfkc93/EmTLvS+3WTGdIn9H6OiCiYe0v39vHnQkKXATo6RYXmgAo38KUKc+Ktukr1EDIk/TKpQH3enYnN8ChZGU0w9ybPa/YGFQIouny9Jl0EBz7zbI890+OUxI2A2Td672+MBEOXKtATzj/296EZUkJyzAwEqeNUX+5M5zFw31JVAb0zwgDZs2DWDXBkg+8Q1qlXdm/TDBp/9EspJS32tl7DsWItJmqa9UqIRhPKDEQd60shxJNCiA8AhBCThBA+9A4HRAnetUZyAB9C7iHMhHPg3D9C+RYYfRrMu13dAI6cD1/7r0o474txZ8H5j6ibzYwpcOXz6rjz/wxzvq2ShMefC2f9Fna9rX44L35M7Xv1iyqBMilf2THhvIC/Zc0QE5WoPu9ZN6i+MOki+PqrKgG3nVGnwEWPQfIoSJug1LCufhmyZkDiSNV3xp0N6ZNUXtHsG1ROSJS7Fo3RBPNvh8U/VWEs+SfBN15TggjJoyB9sspvyp0blH+BRtMjUQmqL8++UfXtgsVq7HW5VF9OyIXx58EZD6jn2XOUWmHWCSo88bw/QtV+OPVeNbGTOh4ufwry5gf7nWl6wO50YTQITMaeb2HiLRHDIydESu9QQY1mGCGk9Lnw0H1H5Xz8B7hHSjldCGECNkkpe81SFULkA+/2oI51HnAHSh3rROCvUso+73Jmz54t169f3y+7h4yWGjVrHBkDdUUqBCA6+RjOYVLHttPmVEow5ng1s21rUDelxk4z1LZGFYI10Otp+oOv1TqfBLxftjlVSJUlXq2y+aKlFgwGJW4AqtCls1UpqQFY61V/SsjtWUWtqVKpDrUrurXUgDB6HBZNKNDvfgkhOmb6mzanUsSKSlZ91eVSY7E5HmLcY2NzlQpzNcd6H9tSq1ZHpEuNs1GJQ27+MCLgY2ZVk53T/ricx78xq8d96lpaufv1bWy+78we9wl5KvfCC1eqfj3pYrjgkd6VNjW9MaAxUzM0DEQdK1VK+bIQ4m4AKaVTCNHW2wFCiBeAJUCqEKIEuA+IcB//OPA+ygHZj5LovWHA7yBU6OwAJOcP/hztGE1KH7+dWB/L1xYdfnVcYDT5/vw7E53kvW2Og87+SlRC385E12to51YTDhhNkNypfq7B0H0sjkn1fWzX740mpGmyOYmJ7DkUC9RKSKPdibPN1euKScjisCkHZPy5ULAE1jwO/7tSreKZIoNtnUbjFwbihDQLIVJw52wIIeYBPjJZPUgpr+7jdQncPgAbNBqNRqPRHMc02Z1E9eGEGAyCeIuJmpZW0uPCUKhlw9MQk67CaAEW3AnLHoSl98I5D/V6qEYTLgxkeuAHwNvAKCHEl6jaH3cGxCqNRqPRaDQaHzTYHET34YQAJEZHUtEQhvkULhesfgymXOZpMxhVfbAdr3sLjGg0YcxAnJCdwBvAOuAo8C9gbyCM0mg0Go1Go/FFo81JVGTfgRzJMZEcbQjDullFq1SOUloXdU1zHMy7Dd6+U9Wy0WjCnIE4Ic8CE4AHgb+hqpw/FwijNBqNRqPRaHzRaOu9Wno7SdERlNWHoROy7RUoOLm7zDooaemUsbDi4aG3S6PxMwNxQsZLKW+SUn7uftwMjOvzKI1Go9FoNBo/0djPcKyk6EiO1PooZBnKSAl73oORC3reZ+Z1sP5JqC8ZOrs0mgAwECdkkzsZHQAhxInAl/43SaPRaDQajcY3jbbeq6W3kxZnpqimZQgs8iPlW8FohoScnveJSYWxZ8Hy3w+dXRpNABiIE3Ii8JUQolAIUQisAhYLIbYJIbYGxDqNRqPRaDSaTtS2tPZrJSQ9zsLh6jDLndj3CYyY0fd+ky5SSeqN5YG3SaMJEAOR6D07YFZoNBqNRqPR9IN6q4PUmB4KtnYiK8HC4ZoWpJQIX/kVocj+pTDmjL73syRAwWJY9yScek/g7dJoAkC/V0KklId7ewTSSI1Go9FoNBqA+hYHMea+51DjoyIwCEFFY5jI9La2QNlmyJzSv/3HnQ0bnwFXr3WjNZqQJQzLiGo0Go1Gozleqbc6iDH3HY4FkJcSzc7ShgBb5CeK10DyaIiI7t/+SfkQlQQHPw+oWRpNoNBOiEaj0Wg0mrBBOSH9iyYflRrDxsO1AbbITxxaCRmTB3ZM/kmw9ZXA2KPRBBjthGg0Go1Gowkb6q0OYvvphEwakcCyvZUBtshPHFoOGVMHdkzeSbD3A2hzBMYmjSaAaCdEo9FoNBpN2NBg678TMjErjiN1VnaU1gfYqkHS2gwVOyB9Qt/7diYmFeKy4PBXgbFLowkg2gnRaDQajUYTFtidbTjaJGZT/25fTAYDV83J5bqn1vL6xhAu7le8RlVCN1kGfmz2LNj7of9t0mgCjHZCNBqNRqPRhAV1LQ7iLaYBSe6ePDaN750+jgff38WGwzUBtG4QHFwB6ZOO7dgRM2HfUv/ao9EMAdoJCQAulwy2CRrNsEN/r0ITKfXnohk6altaiY+KGPBxo9NiOX/aCJ7+stD/RvmDg59D5gDzQdpJGQPNFdBQ6l+bNJoAM5BihZo+qGq0s3xvJa9sKGZCZjxXzM5h8oiEYJul0YQ1hVXNvLetjM93V3D6xAzOmZpJXkpMsM067rE52lhXWMOzqwoxGgxcOz+P2XlJRJr6J52q0RwLtc0O4vqZD9KV2XlJ/OzNbbhcEoMhhIoX2uqhai+kTzy24w1GyJwOh1bA9Kv8a5tGE0C0E+InpJS8uK6Ihz/eC8DqgzW8vqmEN76zkNHpsUG2TqMJT2qaW/nBy5vZWFQHwPrDtSzfW8nj35hJQnRkcI07zll7qIZrn1rbsf3RjnJe+PY85o1KCaJVmuFObUsrcZaBr4QApMSaiY40cbCqiTHpcX62bBAccodiGQcxpmVMhoPLjskJaXY089S2p/is+DPsbXYmpUzisrGXMS9rXvhUmteEJTocy0+U1tt4bNkBr7YGq5Nd5WFSJEmjCUEOVjZ1OCDtrDpYzcGq5uAYpAHUpMtzqwu7tBHaib+aYUFtS2u/a4T4YlRqDNuOhJhS1r6PIWv64M6RORUKvxjwYRUtFVz57pXsqN7BleOv5OZpN5Melc4Dqx7g+g+vZ0/NnsHZpdH0gl4J8RMCMPiYMdCzCBrNsdPT18fXd00ztJgM3eewfLVpNP6kpqmVuH5WS/dFTlIUu8saYYYfjRoMUion5NT7BneehFywN0J9CSTk9OsQe5ud2z65jZnpM7lg9AUd7dmx2SzOXczykuXc+NGNXDHuCr5zwncwG82Ds1Gj6YL+xfATIxKjuOu0sV5tKTGRTMqKD5JFGk34MzotlgWjvcN7ThmfTkGqzgkJJkIIrp2f5+UkGgRcMjM7eEZpjguqm+3EHmM4FkB2YjR7jjb60aJBUrYFDKZ+Ow49IoQKySpa3e9DHtv0GHGRcZw/6vxurxmEgVNyT+GXC37JlsotXPb2ZWw8unFwNmo0XdArIX7kilk55CRZeGdLGWMzYjl3ahaZCRaklHpFRKPpBYfThUR2S2pOjI7kd5dN47PdFXy5v4pF49JYPC7tmNRxNP5lVl4SL3x7Hq9vLMFkMHDxjBFMyQqhOHvNsKSqqZWRydHHfHxWgoXXN4VQOOeON2Dk/J6XfQdC2gQVkjX18j53Lawv5NV9r3L/gvt7vT9JNCfynenfYcPRDXx/2fdZOGIh3535XTJiMgZvr+a4J+BOiBDibOARwAj8W0r5UJfXlwBvAYfcTa9LKR8ItF2BICkmknOnjuDcqSMoqW3h9Y1H+GhHOfNGpXDVnFzGZugfaI2mM442F+sLa3hixUEabA5uXFjAyWO9nYzc5GiuW5DPdQvyg2eophuRJiPzRqUwIzeRLSV1PPLJflzSxbdPHsX80SlEReo5Lo3/qW5qZcogVCcz4i2U1dloc0mMwVbIcrXB1pdhyd3+OV/6JFj3r37t+uimRzkj7wwSzH3/L4UQzM6czeTUybx38D0ufutizht1HtdMvIZRCaMGa7XmOCagvxJCCCPwd+AMoARYJ4R4W0q5s8uuK6WU3dcDw5Qmm4N73tjO8r2VAOwobeDTXUd58ZZ5ZMZHBdk6jSZ02FJcx9f/vYb2EiAbDm/i0WtmcP60EcE1TNNv1h+u5ev/XtOxvepgDU/fMIcl49ODaJVmuFLdbB/USmikyUBclImyeis5Sce+ouIX9n8C5jhILvDP+VJGQ12Rkvy19OxcFNYXsqpsFQ+d/FCP+/giyhTF5eMu5/S80/ms6DOu/+B60qLTWJyzmFkZs5iWNo24SD3Zquk/gc4JmQvsl1IelFK2Ai8CFwX4mkGnsLqlwwHp3HagIoSWgDWaEGD53kq61iB8YvkBWlqdwTFIM2BeWV/cre2/qw8HwRLN8UBts6qYPhgy4iwU11j9ZNExIiWs/CNM8OP8q8EEqeOgZF2vuz2942mW5CzBYrIc02USzYlcOvZSfr/o91wy5hLKmst4ZOMjnPbKaVz+9uX8c8s/qbJWHdO5NccXgV4vzwY6/0KVACf62G++EGILUAr8SEq5o+sOQoibgZsBRo4cGQBT/YfJIBBCjTFd2zXDi3Dql6GIxUdhuxhzBEadQzVohqpvRvsIuxqMhKpmeDOYfimlPOaK6Z1JizNTUtsCBLGmzc63oOkoFCzy73nTxsPh1TDmdJ8v19vr+ajwI3618FeDvpTRYGR88njGJ48HwOlycqDuAGvK1/DMm89ww+QbuHHKjRgNuoCpxjeBXgnxdSfR5dacjUCelHI68DfgTV8nklI+IaWcLaWcnZaW5l8r/Ux+ajRfm53r1TYnP4kxumjhsCOc+mUosmhcGpYI72HoO0tGYY7QP1qDZaj65qWzsr0mWIwGwddP1A65xjeD6Zf1VgeWCCMRxsHduqTERlJc0zKocwyK8m3w3g9g/h2q2rk/SZsARV/1+PJb+99iaurUfuWCDBSTwcT45PFcO+lafjHvFyw9vJQ7Pr0DqzPIq06akCXQ01UlQOe78RzUakcHUsqGTs/fF0I8JoRIlVKG7Vpeq1PygzPGcOqEdErrrKTFmpmem0BKbHeN7eomO442F5kJvnNFpJQ02BxER5oGPfBqNKHG1JwEXrllPkt3HaXJ5uTMyZnMyE2k2e6g2d5Genz/wwWabA5MBgOWSPWj3tLqRErPrPyxnLMvWp1t2Jwu4gchGRoudP3/VjRYMQjBhIw43rpjIe9vK8PRJjlzUgYn5CZidbThcrmIMQ///41maKhqspMYPfj+lBprpqg2CE5IazOsegxWPQon3qocBn+TNhFWPgxtTjB63+JJKXl5z8tcPfFq/1+3C6lRqXx/1vd5Zscz3PXZXTx2+mNEGPRYoPEm0E7IOmCsEKIAOAJcBVzTeQchRCZwVEophRBzUasz1QG2KyCU1ll5Z0spL60r5lsnFbDvaCPL9lYyLSeBrEQLucme2gZ1zXZW7q/myS8OYXO0cc2JI1k0NpX8VM9qSWFVMy+tL+aDbWXMykviWycVMGkQqiAaTSgyNSeRqTmJHdtf7q/kXysPUVTdwjlTMrnwhGzGZ/ac7Fjb3MrSnUf59xcHSYqO5IdnjKPJ7uTvn++nxdHGLYtGk5Vg4e/LDlBS08L507K4YPqIQanVSSnZcLiWx5bt53B1C1fPHckF07LI6GEyIZypbrazdMdRnvziECmxkfzojPHsOtrA/9YUYTYZuHhGDpsO1zAzL5lDVU00WB2s2FfFP5btp8Hq5OZFozhtYjqJ0ZHBfiuaMKeysZVEP8hzp8Wa2VRU6weLBkDhF/DaTSpn45w/QHxWYK5jjoWYDCjfCtkzvV7aVLEJh3QwNnFsDwf7F5PBxPWTr+fvm//OQ2sf4hfzfjEk19WEDwF1QqSUTiHEHcBHKInep6SUO4QQt7pffxy4HPiOEMIJWIGrpOyaTRH6tLkkT39VyBMrDnL2lExe21jCxqI6QCWlryus5dkb53bc+KwtrOXOFzZ1HH/vWzv4zcVTOpyQJpuDX76zg2V7KjvOsWJfFW/ctiD4ih4aTYDYeLiWbz+7gZbWNgD+vuwAVc2t/PLCSURF+B6ulu4s5yevbevY3lRcx28/2N2x/b2XNvPDM8ex5mA1dqeLv362nzqrg5+fN4lI07GtLu4qa+Dr/16D3ekC4Nfv7aLR5uR7p48ddjWBPtxWzj1vbgfgaIOJPUcb+cWbnrS9zcX13H3OBO57ewd3nzOBfRVNPPTh7o6cuB++soU/X3kCl8zQhQw1g6OqaXDKWO2kxEZypM7mB4v6SdEaeOkbsPB7kD0r8NdLn6CKFnZxQl7d+yoLRywc0jHKaDBy09Sb+NXqX7EgawGn5Z02ZNfWhD4Bj++RUr4vpRwnpRwtpfyNu+1xtwOClPJRKeVkKeV0KeU8KWXPwYwhTFm9lWe+KgRgXEZshwPied3G3k5VWpftqeh2jpfWF1PTbAeguLalwwFpp7LRzv6KJv8artGEEHvKGzsckHZe31jCoUrfynKNVgdPrDzUsT0yOZpdZd2rIX+2q4ITC5I7tl9aV8yhqmP/Lu0ub+xwQNp58otDlDcM4Y3NEFDf0sq/Vh7s2L5qzkhe23ik2347yxrIT4nmQGUThdXN3UQ5nvzioFY80wyaykY7Cf5wQmLMVDaqWiEBp7UZXrtR5X8MhQMCKiSr8AuvpmZHM58Vf8aCEQuGxoZOREdEc+OUG3lg9QPU2eqG/Pqa0EUnGfgJk8FAlDtWWiDwJYTVWQkozkcMebzFRIRBfSQmo8Gnmpb5GGduNZpwwFf/joowYuohH8poFCRGeVZIrI42YszdEz1jLSYv5yY60kiE8dhnA33ZGWM2DjsFPJPR4HXT12BzEGfxoWgWacLqaMNsMhAd2f31hKhIrXimGTRHG2w+fzsHSqTJQJwlgorGIZg0WPUYJI+GXF/CoAEiYzIUr/aS6Pyo8CMmJE8ISEJ6fxibNJZZ6bP404Y/BeX6mtBE39H6icwEC3efrZLMlu+t5KITvEMPThyVzIQRnhj0ReNSien0Y20QcO38fOLcP/j5yTHcdLJ3AaN5o5IZp6uua4Yxk7LjyUvxDje87ZQxPfb76EgTd502jvb728pGO/kpMV43wkaD4IxJGWzoFAN+56ljGZV27N+lKSMSGJHoneD+03MmkBbnv6T3UCDGbOJ7p4/r2H55QzFXzsn1qjQdFWFkZEo0dS0ORqbEkBprJraTRK9BwG1LRmvFM82gOdpo80tiOkB6nJmS2gCrNjmssPoxmH5VYK/Tldh0MEZC1d6Oplf2vhKUVZDOXDTmIpaXLGd71fag2qEJHbSYew84nC7qrQ7iokxICU02J0kxkV4/vg1WB21SkuROuDxv2gjyU6MprrWSHmvhpDGpbCquZXxGHHMKkslO9NxcLRyTxhPXzmbNwWqsjjbmj0phXkFSx+sRJgPfPnkUC0encrTRRlJ0JOMz43wqbGk0PdFkc9Da5iI5Zuj6TauzjXqrk4QoE5E+6oD0xoTMeB69egarD9ZQXNvC3Pxk5hYk0WJ3UtFkJyPWTFSXGhTzRiXzyi3zWbGvkoSoCE4ek8aCMSms2FuJzeFi8bhUIk0Gfnr2BI7UWZk3KoU5+ck9WNA/8lJjeO7GE/nqYBVldTYWjE5hxsikvg8MQxaMTuHt2xdQa3UQbTKSEBXBi98+keV7KokwGRiTHktpnZV/fH0mrU4XucnRLBqXxlf7q2myOzl5bCrTcxOD/TY0w4CKBjvj/TQRlxpr5kitlTn5fjmdb7a/BqljISG37339TeYUKFwJaeM5UHeAI01HmJY6bejt6ER0RDQXjr6Qh9Y+xHPnPDfs8uc0A0c7IT7Yd7SRf608yOd7KpmTl8SpE9P5y9J9nD4pg+sW5JEeZ2H53kr+/MleWp0ublsymrMmZ9Jkd/Ll/mpeXl/CyJQorpkzkoYWB6v2V/lU91k4JpWFY1J7tKPe6uDjneV8uOMoM3ITufO0seQMz/scjZ9pdbr46kAVf/x4L7UtrdywsIALpmeRHuCZ+r1HG/jn8oOs2FfFwtEp3LpkNBMy4wd0DrvTxfrDNdgdbaRER5KRYOHJlTvZUFTL3PxkvnVyATM73fBHmozMzk9mttuxqGu28+nuCpbuPIrTJYmzmDhnaia3LB7t1/c6Oj2W0cdB7Z/SOisr9lVxpM5KaqyZNzcfITbSxNUnjmRPWQOTshIYlxHLA+/uwiXhzlPHcPrEDL69SCv5afxLRaPdbyprQ1IrZMN/YOzZgb1GT2RMgQOfw5yb1CpI1oKQKBp4UvZJfFb0GZ8Xf86pI08NtjmaIKOdkC7UNNu568VNHcmt728vZ1NxHWdNzuTprwo5XN3MdQvyue35jR3H/N9r27BEGNlaXMeTXxYCUN5gY0txPbefMoY/Ld3LusN1PHfT3H7fkDVaHfzs9W2sPlQDwMc7j7KusIa37jiJkclaHUvTO1tL6rjh6XUdIcG/encnQsCNCwt6P3AQVDbaue35TR3iCW9uLmVjUS2v3rqg37U59pR7q06dPSWL77+0uSNs4r1tZewqa+DpG+YwMiXG5zlWH6rhh69s7djeWlKPJcLIN+blDebtHbe8t62MJ1Yc5Bvz8vjbZ/s72u99awc/PWcC335uPT89ZwIH3OIBP3h5C//4xkzOmRIgCVLNcUtlo90vEr2gqqYXVvsWvPALNYeg+gCcMjtw1+iNzOmw/ilsrc28e+Bd7j7x7uDY0QWDMHDJ2Ev484Y/szhncUg4RprgoXNCunC4uqWbuk5ZvY14d/JrUU0L728r63bcf1cfZl+F93F2pwunS91MVTYNTNmqqLalwwFpp7bFwQGtjqXpB+sP13ZTKPrPl4eoaW4N2DUPVzd36+NFNVYOVfX/h37v0SYv1SmDoFvc9sGqZvb18j34ZFd35blX1hfTZHP02w6NorSuhZfXlzB/dAqf+vi/HqxsJjPews7SBgpSPU7hi2uLhtJMzXGAzdFGs93pF4legIw4C0WBXAnZ8QbkLQBDkOZ6Y1IhKolVG/9JQUIB6dHpwbHDB9NSp2E2mnn/0PvBNkUTZLQT0gVLhBFfYYrtyi6tThdpPvIy0uMstLm6NWM0eP7F0QNIzLSYfKv3RPlQntFoupIQ1f2HLyXGHFB1NUsP/bundl9Eddm3p2RmXwpM7aTGdA/XSIk1D0oN63jFYjKSHB1Bg81JUkz3m784i4kWh5N4i4kmu0eCN2sYFm3UBJfKRjvJMZEY/JRHkBFv5nB1IJ2Q12FkcBPBZdYJlG9+liW5S4JqR1eEEFw85mIe3fQoDpeeHDqe0U5IFwpSY7qFrJw6IZ1NxXUAXH3iSM6ZmuWl/hJpNHDDwnwun5Xjddyo1BjqWtTM8+JxaUzI6n9s/MiUaG4/ZYxX2ynj0rQ6lqZfzMlP9nKWDQJ+cMY4YsyBm5UblRrDN+aN9Gq7YlYOo9P6nzcxaUQ8EzuFLG4rqeP8ad5hPZfNzGZiVs/fg1MnpBNv8bzPCKPg2vl5mHsodqjpmeRYM7cuGcO6Q9WcMSnDS5gjMTqCxOgIpAtyk6OpbFQ1jswmA1fOCUIirmZYU1Zv86swS0qMmTqrA5ujre+dB0pdMdQVqbyMIFIUn8bsugqmpAbXDl+MTx5PclQyb+57M9imaIKICMPi5MyePVuuX7/e7+dtsTsoqrFiNgkOVbWwq7yR/JRoshOiaHI4iTcbSYgy48KFtdXFmkM1ONsk80YlkxlvxiVV6EhZg42oCAOpMWYabE5MJkF6rBkJZMVbcEqJtbWNtDgLZXVWHG0uCtJiOVTZRITRQI4756OupZXNxXXsKG2gICWGydnxRJoMJMdEYh6g6pDmmOn3tFug+uWxsr+ikQ2Ha2m0OZkxMpFpOYlE9FBvYzA0Wh00t7aREhtJvdXB+sIa9pQ3MjYjjjn5ScRbTJTU2oi1GMmIVzPkO0vrMRoE490OR3WTnTYpSXeHSNhaHdicksQoE3anZGdZAwcrmxidFsv0nETSE8yU1tqIs5g68k0OVTYRYTKQkxTNpqJayuqsuFBhFzNyEzF1WQVqaXVSb3WQFB2BxYeDIqWkotFOpNFAko/VlSAzoOng/vbNNpekstFGVKSJhKgIXC4XRdUtlDVYabI5SYiOxNHmItJowGwyEGEUCCFwucDqcFDd7CQ3OZqJWfFen6nmuCIgY+Zbm4/w8vpi7jhl7DEb1pX/e20r//zmLCYOYIKwX6z5J+xfCgu+69/zDpDfr3mQ7+7fwK6rn8ER07MITrA4UHeAf237Fx9c+gGRxoCPsXopPATRU4NuNhfV8t81h/lo+1Fyk6P5wRnjuHVRAV/sr+b+d3eyr6KJUyekMWNkEl/sq2L+6BT+u/owLpeKVc1JiiInOZpX15fwwfYycpKiuH5hPk8sP0hyTCS3LhnNE8sPcMnMHP7z5SFK621cfEI2SdERxEdF0Li5lP+uOYwlwtihtpUSa2bJ+HSWjE9na0kd97yxnc3FdSwel8Z3Tx+rV0U0vTImPY4x6YHrI1JK1hbW8OD7uzhY0cxls3I4Z0omL6wtZk95A2PT40iOieTtzUd4d2sZOUnR/PqiySzbW8nza4qIijTyf2ePx9Em+dPSvVhb2/j2yQVMyU7gwfd3U1LbwlmTM/na7BxeXV/CvopGxmfGkx5n4R8rDvDeljLyUqK557yJfLm/mv+tLSLWbOK7p40l1mLkwQ92Y3O0cevi0RSkxpAa55lF3Xaknj98tJuNh+tYOCaF758xzks0orzeysvri/nPl4UkRkfw07MnsmR82rCudVFc08J/vjzEqxtKyE6K5t7zJ/LZrgpm5yexsbiOrHgLW0rqeWFtMdFmI9fMHcmGw7VMz01kR2k9s/OSyUq0sO9oA3vKG3j4Y/WZ3rxoFJfOzB52NVQ0Q0tpnY1kPyljtZOdGMX+iib/OyE734aCRf495wDZVbObo7YaWjKnknToCyqmXBxUe3wxOnE02bHZvLLnFb4+6evBNkcTBHQ4FlDXYucfyw/w6oYjNNqd7Cxr4LbnN7L+cB23Pb+RTcV1NNmdvL2ljHe3lnH+tCx+/d4uCqtbKKpt4Y9L9xIfbeL51Yd5aX0xDTYnO8sa+dnr27l4Rg5rC2v54ctbuOnkUfzsje3sLm+iwerk2VWHKaqxEhtp5C+f7qOqqZWSWis/e2M7aw5Vd9hXXNPCdU+t5Yv9VTTZnby3rYzvvriJ2gAmGWs0fbH3aBPXPrmWLcX1NNqdTMiM44evbGH53krKG+ys3F/F91/aTITJSIPNCUjWFNby18/2U92s+vqRWhs/eHkLJbVWqptbeejDPXx1oJojdVYabE5e2VDCv784RHNrG+UNdpbvreTHr23hhJxEGu1OyuptfL67kkc/309NcytFNS388JUtHKpsoaTWSlVTK79+bxef7/EkVR+ptXLj0+tYsVd9nz7acZTbn99IVZO9Y583Nh3hT0v3Udvi4FBVC7f8dwNbSuqG/p88RDicLv6x/ABPfVlIg81Jo83Be1vL2FHWwPbSBj7cXk6z3cmjnx+gurmV4horv/twD7Pzkvnjx3uZnpPIb97fha21jcomO997yfOZ/vaD3Xy882iw36ImzCmpbSHZzyuSWYkW9pQ39r3jQLDWQdkmGDHTv+cdAG3SxYu7X+Ck7IU0jZhGyp6lQbOlLy4afRH/2vYvWhwBlkvWhCTaCQEKq1pY2uVHsrXNRWFVM82t3vGiGw7XYvURQypdgne3eqtmOV2S1ja1b22LgyN1Ntpc3uFv728ro87qpCvL9lR2PD9U3Uxti3fy1q6yRopq9ZdWEzz2VzR6KVmZjKKbklVZva0jSf6mkwt4a/ORjtdGJFjYX9ld5eqz3RWcWOApJrh051Hmj07p2C6usWJyJ5nPH53CJ7u63+Aermn2yol5bvXhjtjvwurmjvyFdg5UNnco5dQ023l+TXd1p/WFtd3ahgtHG228vK64Y/vksal8tOMo187L483NR7hiVi5vbSntdtyByiayEiwdIaMf7jjKWB+rb8+tOkyzvfs4p9H0l+JaVafGn4xMimZ7ab1fz8m+pZA5DSKCt/L3efHnAExInkhz2njMjWVY6or7OCo4jIwfydiksTy387lgm6IJAtoJQan3JPiQ/YuO7B6tZokwEOlDYUgifcaNd1bHioroflxPg2pGp7oKMT6UgEwGMSC1LY3G33RNcjebeleWq2ywk94pJKrJ7vT5vUuNNVPb4lnlS4qO9FJeEoKOnKjallavMKt24iwRNLd6jslNjsbkTqqOMXf/3hiER3HLbDKS6aOuSUpsyOWF+A2zyeD1/mpbHKTGRVLb4iAt1szRBpvXZ9dOfFQETTYnSdGRNNgcZCVY3Kte3uQkRWl1Ms2gKKlpIc1HHxwM+akx7DjS4NdzsustyJnj33MOgNLmMt7a/yZn5p2lkiAMRupzZpO2452g2dQXF42+iGd3PkutbfhO9Gh8o50QYEJWPD84Y5xX25TseApSo1k4JsWr/dr5+bS0tnndPFkiDMSZTfywyzkmZMZ1zLieNTmDSJORMZ0qLAsB35yXx6i0GC/p1OSYSBaPS+vYHpsex6Uzsr3OfeepY8jvoVibRjMUTBoR77VisXJfJVd3UUW6cnYOXx1QoYW/X7qH6xbkE+lOjm+wOUmLjSS1081vpNHAuVMzWX/Y82N0+ymjeafTLPzVc3JZuU+tFK46UM0lM7K9bnDT48zEW0y0uFcxzSYD31pYgMl93TFpsVw529vO7ywZTYH7+xRjNvGDM8Z1OC0AIxItzMlPZriSFmfhvgsmd2x/tquCa04cya/f38nNi0bx0voivn5iXsdnB5AaG0m8xYTRKMiIt2B3uDhzUgaFVc2kxHh/prcuHk2kFtPQHCNSSkrrrX4XOUiPM+Noc3Gkztr3zv3BYYWDyyD3RP+cb4A0OZr568ZHOCn7ZFKiPONVXd48Uvd+jNEemnXGMmIymJs1l79v/nuwTdEMMce9OlabS3K0wUabs43dFU3sr1A/oJNGxDElO5FdpfXsKGugosHO6LRYJJLyeivjMuLYX9mMo00yJy8RCUQaBUfqVVHClJhIMuLNbD/SQGaChZHJUdQ0t5IYHUlZvY0mm5OcpChqmu24XJKMhCj2Hm0iwiSYmp3ACblJXnZWNtrYVlLPkTorBakxTM1JICFq+M7MhhBhq441FJTVWdlSUkdVUytj02NJiYlgZ3kjR2qsjEiKYlJWHM22NuxtLowCMuIiKKy1s7uskcgIA5Oz4kmKjmTbkTpsThdTRiQgXS52ljVS0+JgdFoM+SlR7CxrpLTORnZSFBMz4iiqs3LA/T2bkZvA0aZWdpY2YIkwMi07gRizkS0l9TjbJJNHxDM5O8HL7qomO1tL6jlS20JeSgzTchKIijBS2WQn1mwizhLBjtJ6dpQ2EBNpYlpOAvmpIeX0+10dy+5oY9uRevaUN5IYHcG49FjKGuw02RxEm01UNdpIibNwsLIJS4SR9DgzVY2tpMZGUt5gY0x6LM02B7kpMZgMBq/PdPKIeISf6jtoQh6/j5lHG2yc/ZcVPPb1WYMyzBd//Wwfl83M6Saxf0zsehdW/AHO/PXgzzVAmlqbeHjDH8mKyWRxzuJur2duepGmzEmUzb52yG3rD42tjfziy1/wzNnPMCZpTN8HDBw9AIUgx7UTUlpn5ZlVhTz9ZSHxlgjuPncCZ03O7LOWQr21lbc2l/KXpXv50Znj2FfZzAtri4iJNHHHqWM4e3IGWYnRHfuvL6zhvrd3sLOsgSXj0vjpORM6pEk1IY92QgbAmoPV/O6j3ewqbWB8Rhw/P38S//7iIEt3VpCTFMVPzhrPaRMysIRY0c39FU388eM9fLSjnNHpsdx/4WTmj0oJ5RvngEj0AhTVtPD48gO8sr6YtFgz9184mcXj06htbuW5NUVMzoxjc0k9L6w9jMmgVjlOn5jOqAAqsWnCCr+PmV8dqOI37+3i5+dNGpRhvvh8TwWFVc08ce3swZ/sleshNhMmnDf4cw2A4qYS/rbpb4xOGMWinMU+P4CI5iryvnyU7V/7d0jK9QJ8cvgT9tTu4T9n/ScQY2/IDubHM8d1ONZbm4/wz+UHsTtdVDbZ+cHLW/qlgLPuUC33vrWD1DgzRxtb+c+XhdgcLqqbW7n/nZ1sOOw5x6HKJq57ai07ShuQEj7fU8kPXt7iFfOu0QwHDlQ28r2XNrPxcB1Wh4upOYn8Y9kBPtx+lDaX5HB1C3e9uJn1h2uCbaoXTTYH9761nQ+2l+OSsO9oEzf8Zx17j4Zm6EIgcba5eGrlIf63pghHm6S03sbN/93A9tIG3ttWztId5RTXWvnnioM02NqoaXHw4Ae72VLi5+RejaYTByqbyUoITKL3nLxkvjpQPXi1SXsj7PsE8k/yj2H9oE228cGhD/jd2oeYmzmXxT04IACOmFTq8uaTt/wvEKKTz6fknkK1tZp3DoZu/orGvxy3TkhtSysvrO2uFrH2UN83SB/uKAfgohOyeW9bWbfXVx/0yOseqm7pprC1o7SBI7V+ikHVaEKEQ5UtlNXbOrbnjUrms07SuKDCHw9VNQ+1ab1SVm/ryFtpx+50cbDq+HNCKhvtvLLBe1yUEvaUNfLi2iKuX5jvc8xbvreyW5tG4y92lzWQlRAVkHPHWkzMG5XMo5/vH9yJdrwJmVPBktDnrv7gUP0h7l91P+vK1/H1id9gSsrkPo+pHnMaloYjZGx9ZQgsHDhGg5HrJl/HH9b9gYqWir4P0IQ9x60TYjEZyUuJ7tben9mWAndseFmdlezE7gNjVqe2eEv30C6zydBnyJdGE27ER0XQKZebJrvTp/pbrI/vRDCJijT6/J7GW7ordw13oiKNjPAxpiVGR5CfGkNhVRM5Sd1fz/bRptH4ix2lDT5/r/3F5bNyeWdLKb/7YDdbiuuwtnaX4e8VKWHdv2DM6YExsBNWp5Xndj7Hnzf8hWlp07li/NdIMif261hpNHFk1jfJ2vwyyfs+Dayhx0hefB5Lcpfw05U/pc01wM9BE3Yct05IVKSRu04b66VKlZcSzdyClF6OUpw+MZ3U2Ej+t66Ia04ciaWT9G5WgoW5nRSDxmbEcdlM74S3u8+ZQF5y4AZUjSYYTMqK44aFBR3bj362nx+dOc5LtndWXiITQywfKicpmnsv8J5FPGNSBhMyj78ch8ToSH5+/iSMnbzJKdnxTMtJ4NbFo3lmVRFXzM71kg1PizWzaGxoxphrwh9Hm4s95Y0dk3+BICEqgnvPn8TByiZ+8PJm5vzmEx79bB/9zpktWg3NVZDt/8T5zmyu3MzPvriHGlsNN0y5nikpkwec6OCMTqZ47rcY+eVjpG1/OyB2DpbzCs6jubWZv236W7BN0QSY4zoxXUrJrrIG9pQ3YokwMnlEAiP7OdtyqKqZHaX1REUYiYowsr+yiUijgQmZcZww0lvZqrrJzvYjDVQ02hiZHM2U7AS9EhI+6MT0AVBWb2VrST2ldVYyEyxMyYxnf1UzhdXNJERFMCEzjkkjhiZcYSBYHU52ljZwqKqZlBgzU7IT/F6TwM8ELDHd2eZiZ1kD+442EWcxMSU7oWN1ZHd5A6V1LVhMJvZXNmEyCMZlxDF7GMsXawaMX8fMzcV1fO/FTfz20mmDNqy/VDfZ+cun+zhrciY/Pmt87ztLCU+fDyNOgHFnB8Se+tYG/rfzefbXH+DMvDPJix856HNGNFeRs+4/1OfMoeik25DG0FLbbLA38Nu1v+WWabdwxfgr/HFKnZgeggTcCRFCnA08AhiBf0spH+ryunC/fi7QAlwvpdzY2zn1zZ5mCNFOiCYUCZgTotEMEr+OmY98spe9R5v4xry8QRs2EOqtDn7x1nYeunQqp03M6HnHnW/D0l/A+X8Bg38nF9ukixUlK3h93+tMTp3MwhELiDD4L0zU4LCSueUVTK1NHDj9HmxJQ/s/7oujzUd5eP3D3DLtFq6eePVgT6edkBAkoOFYQggj8HfgHGAScLUQoqvG3jnAWPfjZuAfgbRJo9FoNBpN6COl5M3NpczOS+p7Zz+TEBXBbUtG8+NXt/ZczLDmELz7fZh3m18dEBeSDRUbuffLX7CsZBmXj7ucJTmL/eqAALgioiid9U0asmcw8c3vkrXxeURb6Ch3ZsRk8OM5P+bpHU9z75f30uwILVETzeAJdE7IXGC/lPKglLIVeBG4qMs+FwHPSsVqIFEIkRVguzQajUaj0YQwH24vByTjg5SfNSEznnOnZnL9U2upbrJ7v3hkIzx9Hkz7GqT7p35JpbWS9w99wN0r7+b1va8xb8R8rhp/FRnR6X45v0+EoC5vPodPupOEonVMfeF60na+i8ERGgqe6dHp3DPvHqqt1Zz/xvk8t/M56u1aEny4EOjEhGygs95jCXBiP/bJBrx0IIUQN6NWShg5cvDxkBqNP9D9UhOq6L6pCUX62y8/2lHOd57fyF2njqG2xTFU5nVjXkEKpXU2Zv36E26al8kc2yqW1L6C+ehmmPNtyJmrktJ7QQLFjSXY2qw4XE5a21qxOa00O5qosdVR3lxGcVMJTpeT/Pg8liRPJTMmE4HA3lA6JO/TBjSOP5O42iIytrxC/oq/0JCUR336eJrjR2CPTsQZEY09Oomm5PwhsakzF425iOkN03lz/5v8ft3vyYnNYVraNPLj80mLTiM+Mp6xSWMpSCjo+2SakCGgOSFCiCuAs6SUN7m3vwnMlVLe2Wmf94DfSim/cG9/CvxESrmhl/NWAocHYEoq0PsoEf7o9xgYqqSU/co2PIZ+eayEy2cdDnaGg43Q3c5+90sY0r7ZE+Hwf9Y2+geLlHJKf3bsrV+mXvR/eTETTk5ta2lwIl0CYQiqio4xOr5j0vbxiD9xcts6l9UpXf051iWEQcQa+4486dfZhoYE6aKnVPUTkzOdDYbgiasaIg0Gg7m7Aa2Vrba9P967w8chqcDugYyZmqEh0CshJUBup+0coKtb3599vJBSpg3ECCHEeinl7IEcE27o9xh8Btovj5VQ/z+0Ew52hoONMHg7h6pv9kQ4/J+1jf5BCNFvBYT+9svQe9/nAdBf0eDQs39gdLV/TTCN6YsfdW9y268dkBAk0K7sOmCsEKJACBEJXAV0FaZ+G7hWKOYB9VLK7iV5NRqNRqPRaDQazbAgoCshUkqnEOIO4COURO9TUsodQohb3a8/DryPkufdj5LovSGQNmk0Go1Go9FoNJrgEvCKeVLK91GORue2xzs9l8DtATbjiQCfPxTQ7/H4IVz+D+FgZzjYCOFjZ0+Eg/3aRv8QCBvD4X33hrY/uIS7/cOWsKyYrtFoNBqNRqPRaMKX4MkbaDQajUaj0Wg0muMS7YRoNBqNRqPRaDSaIeW4cEKEEEYhxCYhxLvBtiUQCCEShRCvCiF2CyF2CSHmB9smfyKE+L4QYocQYrsQ4gUhhCXYNg01QohcIcTn7s93hxDiu8G2yRdCCIsQYq0QYovbzvuDbVNvhMPYIIQoFEJsE0JsHoj8aSgQRv02pPtBOIzxgRinhRBnCyH2CCH2CyF+6g87hxIhxFNCiAohxPZg2zJQwuW72xPh9lt0vHJcOCHAd4FdwTYigDwCfCilnABMZxi9VyFENnAXMNtdAMuIkno+3nACP5RSTgTmAbcLISYF2SZf2IFTpZTTgROAs93S26FKuIwNp0gpTwjDWgPh0m9DvR+E9BgfiHFaCGEE/g6cA0wCrg7RvtMbTwPhWp8iXL67PRFuv0XHJcPeCRFC5KAqC/072LYEAiFEPLAIeBJAStkqpawLqlH+xwRECSFMQDR9FLMcjkgpy6SUG93PG1E3IdnBtao7UtHk3oxwP0JS/WK4jw2hQDj021DvB2E0xvt7nJ4L7JdSHpRStgIvAhcN8pxDipRyBVATbDuOhXD47vZGOP0WHc8MeycE+AvwE8AVZDsCxSigEviPO5zg30KI/hZyDXmklEeAh4EioAxVzPLj4FoVXIQQ+cAMQrRwrTu0ZTNQASyVUoaknYTP2CCBj4UQG4QQNwfbmGMlhPvtXwjtfhDyY3yAxulsoLjTdglhdBM8nAjh726vhNFv0XHLsHZChBDnAxVSyg3BtiWAmICZwD+klDOAZiDsYmd7QgiRhJr9KgBGADFCiG8E16rgIYSIBV4DvielbAi2Pb6QUrZJKU8AcoC5QogpQTapG2E2NiyUUs5EhaXcLoRYFGyDBkqo9tsw6QchP8YHaJwWPtr0TPYQE6rf3f4QDr9FxzvD2gkBFgIXCiEKUUu5pwoh/htck/xOCVDSycN/FfWDNVw4HTgkpayUUjqA14EFQbYpKAghIlA/Bs9LKV8Ptj194Q4ZWUZoxkSHzdggpSx1/60A3kCFqYQNId5vw6EfhMMYH4hxugTI7bSdw3EYihtMQvy7229C/LfouGZYOyFSyrullDlSynxUktxnUsphNYsupSwHioUQ491NpwE7g2iSvykC5gkhooUQAvX+Qiopcyhwv/cngV1Syj8F256eEEKkCSES3c+jUDcnu4NqlA/CZWwQQsQIIeLanwNnAmGjtBPq/TYc+kGYjPGBGKfXAWOFEAVCiEjU5/P2IM+p6Seh/t3ti3D5LTreMQXbAI1fuBN43j1QHwRuCLI9fkNKuUYI8SqwEaXWsQl4IrhWBYWFwDeBbe4YV4CfSSnfD55JPskCnnEr2xiAl6WUISl7GiZkAG+o+wFMwP+klB8G16QBES79NtQJ6TE+EOO0lNIphLgD+AiltvWUlHLHoI0dQoQQLwBLgFQhRAlwn5TyyeBa1W/C/burf4vCACGlDrHUaDQajUaj0Wg0Q8ewDsfSaDQajUaj0Wg0oYd2QjQajUaj0Wg0Gs2Qop0QjUaj0Wg0Go1GM6RoJ0Sj0Wg0Go1Go9EMKdoJ0Wg0Go1Go9FoNEOKdkI0Go1Go9FoNBrNkKKdkGGCEGKJEKJHDWwhxPVCiEcDcN3rhRAjOm0XCiFS/X0dTfjTVx/tx/GzhRB/7eG1QiFEqhAiUQhxm7+uqQk/uo5Jvez3tBDi8l5eXyaEmO1n23T/1Pitj/bj+AeEEKf7aO/od+7nCzq9NqhrajQDQTshmsFyPdDnYKrRDBYp5Xop5V197JYI3NbHPprhzfWE7piUiO6fmiHqo1LKe6WUn/Sx2xJgQR/7aDQBQTshQ4gQIkYI8Z4QYosQYrsQ4kohxCwhxHIhxAYhxEdCiCz3vsuEEH8RQnzl3neuu32uu22T++/4Y7AjTQjxmhBinfux0N3+SyHEU+5rHxRC3NXpmF8IIXYLIZYKIV4QQvzIPVsyG1XJd7MQIsq9+51CiI1CiG1CiAmD/sdphoxg9lF3f0kUimohxLXu9ueEEKd3mb1LEUJ87L7GPwHhPs1DwGh3f/yDuy1WCPGqu/8+L4QQ3a+uCVWEEPnuz+4ZIcRW92cZ7atf+hqThBD3use57UKIJ47l8xdCnCmEWOUe114RQsS62wuFEPd3He/cY+xSd/s/hRCHhVoh1v1zGBKMPuoeZ193P79ICGEVQkQKISxCiIPu9o5VDSHE2W4bvwAubbcbuBX4vtuWk92nX+Qeuw8KvSqiCSRSSv0YogdwGfCvTtsJwFdAmnv7SuAp9/Nl7fsCi4Dt7ufxgMn9/HTgNffzJcC7vVz7euBR9/P/ASe5n48Edrmf/9JtjxlIBaqBCNSAuRmIAuKAfcCPOtk5u9N1CoE73c9vA/4d7P+7foRNH30cOA+YAqzrdO59QGzn44G/Ave6n58HSHefzW+3o9M164Ec1KTLqva+rx/h8XB/phJY6N5+CvhxH/2y85iU3On5c8AF7udPA5f3ct1l7rEvFVgBxLjb/69T3/M53gGPAne7n5+t++fwfgSjjwIm4JD7+cPuMXMhsBh4ofPxgAUoBsaiJmxe7jSW/hL373mnY15x98dJwP5g/3/1Y/g+TGiGkm3Aw0KI3wHvArWoG66l7okPI1DWaf8XAKSUK4QQ8UKIRJQT8IwQYixq0Is4BjtOByZ1mmyJF0LEuZ+/J6W0A3YhRAWQAZwEvCWltAIIId7p4/yvu/9uwD3jogkbgtlHV6KcmcPAP4CbhRDZQI2UsqnL5OAi3H1LSvmeEKK2l/OulVKWAAghNqNuGL7op02a0KBYSvml+/l/gZ/Re7/szClCiJ8A0UAysAPoawzrzDzUzdiX7mtFopyFdnyNdycBlwBIKT/U/fO4YEj7qJTSKYTYL4SYCMwF/oQaF42osbQzE1AOyz4AIcR/gZt7Of2bUkoXsFMIkdGbHRrNYNBOyBAipdwrhJgFnAv8FlgK7JBSzu/pEB/bvwI+l1Je4l5KXXYMphiA+e1ORTvugdLeqakN1UcGGh7Qfo724zVhQpD76ArgdtTq3D2om7jL6f6D2tO1e8JXn9aEF10/60Z675cACCEswGOoWediIcQvUbPCA0EAS6WUV/fwuq/xbiBjpu6fw4Ng9NGVwDmAA/gEtYphBH7UD/t6o3Of1OGBmoChc0KGEKHUMFqklP9FLZ+eCKQJIea7X48QQkzudMiV7vaTgHopZT0qPOaI+/Xrj9GUj4E7Otl1Qh/7fwFc4I41jUWFv7TTiJr51gwDgtlHpZTFqJCVsVLKg6h+9yN8OyErgK+7r30OkORu1/1xeDKyvQ8CVwOr6blfdu4D7TdzVe6x61ji21cDC4UQY9zXihZCjOvjmC+Ar7n3PxPdP48HgtFHVwDfA1ZJKSuBFNSqx44u++0GCoQQozvZ147uk5qgoZ2QoWUqsNa95H4PcC9qwPmdEGILKu+is0pFrRDiK1Ss/Lfcbb8HfiuE+BI143Es3AXMdifQ7UQlpvWIlHId8DawBRV6sB4Vxwxq5uVx4Z2Yrglfgt1H1wB73c9XAtn4Dk25H5U8uRE4EygCkFJWo8JmtgtP4q8m/NkFXCeE2IoKV/kbPffLp3GPSagZ3X+hwgzfRMXNDwj3zd31wAvu669G3ej1xv3Ame7+eQ4qDKdR989hTTD66BpUyPQK9/ZWYKuU0mvVQ0ppQ4VfvedOTD/c6eV3gEu6JKZrNEOC6NJXNSGCEGIZKllsfbBtARBCxLrj8qNRA97NUsqNwbZLEzxCrY9qhifukL53pZRTgm1LfxFCmIE2d9z+fOAfUsoTgmyWJkCEYx/VaEIBHXuq6S9PCCEmoZaOn9EOiEaj0fTISOBlIYQBaAW+HWR7NBqNJuTQKyHDDCHEDcB3uzR/KaW8PRj2aDRd0X1UE0oIId4ACro0/5+U8qNg2KPRdEX3Uc1wRTshGo1Go9FoNBqNZkjRiekajUaj0Wg0Go1mSNFOiEaj0Wg0Go1GoxlStBOi0Wg0Go1Go9FohhTthGg0Go1Go9FoNJoh5f8BLeaVjvaY2gYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 804.75x720 with 20 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(df, hue = 'species')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3a919e9a",
   "metadata": {},
   "source": [
    "# Load Libararies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "47b4fa83",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import pandas_profiling as pp\n",
    "import sweetviz as sv\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a74f039f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Ozone</th>\n",
       "      <th>Solar.R</th>\n",
       "      <th>Wind</th>\n",
       "      <th>Temp C</th>\n",
       "      <th>Month</th>\n",
       "      <th>Day</th>\n",
       "      <th>Year</th>\n",
       "      <th>Temp</th>\n",
       "      <th>Weather</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>41.0</td>\n",
       "      <td>190.0</td>\n",
       "      <td>7.4</td>\n",
       "      <td>67</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2010</td>\n",
       "      <td>67</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>36.0</td>\n",
       "      <td>118.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>72</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>2010</td>\n",
       "      <td>72</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12.0</td>\n",
       "      <td>149.0</td>\n",
       "      <td>12.6</td>\n",
       "      <td>74</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>2010</td>\n",
       "      <td>74</td>\n",
       "      <td>PS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>18.0</td>\n",
       "      <td>313.0</td>\n",
       "      <td>11.5</td>\n",
       "      <td>62</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>2010</td>\n",
       "      <td>62</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.3</td>\n",
       "      <td>56</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>56</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>41.0</td>\n",
       "      <td>190.0</td>\n",
       "      <td>7.4</td>\n",
       "      <td>67</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2010</td>\n",
       "      <td>67</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>30.0</td>\n",
       "      <td>193.0</td>\n",
       "      <td>6.9</td>\n",
       "      <td>70</td>\n",
       "      <td>9</td>\n",
       "      <td>26</td>\n",
       "      <td>2010</td>\n",
       "      <td>70</td>\n",
       "      <td>PS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>NaN</td>\n",
       "      <td>145.0</td>\n",
       "      <td>13.2</td>\n",
       "      <td>77</td>\n",
       "      <td>9</td>\n",
       "      <td>27</td>\n",
       "      <td>2010</td>\n",
       "      <td>77</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>14.0</td>\n",
       "      <td>191.0</td>\n",
       "      <td>14.3</td>\n",
       "      <td>75</td>\n",
       "      <td>9</td>\n",
       "      <td>28</td>\n",
       "      <td>2010</td>\n",
       "      <td>75</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>18.0</td>\n",
       "      <td>131.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>76</td>\n",
       "      <td>9</td>\n",
       "      <td>29</td>\n",
       "      <td>2010</td>\n",
       "      <td>76</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>158 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Ozone  Solar.R  Wind Temp C Month  Day  Year  Temp Weather\n",
       "1     41.0    190.0   7.4     67     5    1  2010    67       S\n",
       "2     36.0    118.0   8.0     72     5    2  2010    72       C\n",
       "3     12.0    149.0  12.6     74     5    3  2010    74      PS\n",
       "4     18.0    313.0  11.5     62     5    4  2010    62       S\n",
       "5      NaN      NaN  14.3     56     5    5  2010    56       S\n",
       "..     ...      ...   ...    ...   ...  ...   ...   ...     ...\n",
       "154   41.0    190.0   7.4     67     5    1  2010    67       C\n",
       "155   30.0    193.0   6.9     70     9   26  2010    70      PS\n",
       "156    NaN    145.0  13.2     77     9   27  2010    77       S\n",
       "157   14.0    191.0  14.3     75     9   28  2010    75       S\n",
       "158   18.0    131.0   8.0     76     9   29  2010    76       C\n",
       "\n",
       "[158 rows x 9 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv(\"C:/Users/Moin Dalvi/Documents/EXcelR Study and Assignment Material/Data Science/EDA 1/data_clean.csv\",\n",
    "                   index_col = 0)\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "8939253a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[41.0, 190.0, 7.4, ..., 2010, 67, 'S'],\n",
       "       [36.0, 118.0, 8.0, ..., 2010, 72, 'C'],\n",
       "       [12.0, 149.0, 12.6, ..., 2010, 74, 'PS'],\n",
       "       ...,\n",
       "       [nan, 145.0, 13.2, ..., 2010, 77, 'S'],\n",
       "       [14.0, 191.0, 14.3, ..., 2010, 75, 'S'],\n",
       "       [18.0, 131.0, 8.0, ..., 2010, 76, 'C']], dtype=object)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "44ec4b94",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   Ozone  Solar.R  Wind Temp C Month  Day  Year  Temp Weather\n",
      "1   41.0    190.0   7.4     67     5    1  2010    67       S\n",
      "2   36.0    118.0   8.0     72     5    2  2010    72       C\n",
      "3   12.0    149.0  12.6     74     5    3  2010    74      PS\n",
      "4   18.0    313.0  11.5     62     5    4  2010    62       S\n",
      "5    NaN      NaN  14.3     56     5    5  2010    56       S\n"
     ]
    }
   ],
   "source": [
    "print(data[0:5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "a5562cc3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[41.0 190.0 7.4 '67' '5' 1 2010 67 'S']\n",
      " [36.0 118.0 8.0 '72' '5' 2 2010 72 'C']\n",
      " [12.0 149.0 12.6 '74' '5' 3 2010 74 'PS']\n",
      " [18.0 313.0 11.5 '62' '5' 4 2010 62 'S']\n",
      " [nan nan 14.3 '56' '5' 5 2010 56 'S']]\n"
     ]
    }
   ],
   "source": [
    "print(data.values[0:5,:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "1c89507a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[41.0 190.0 7.4 '67' '5' 1 2010 67 'S']\n",
      " [36.0 118.0 8.0 '72' '5' 2 2010 72 'C']\n",
      " [12.0 149.0 12.6 '74' '5' 3 2010 74 'PS']\n",
      " [18.0 313.0 11.5 '62' '5' 4 2010 62 'S']\n",
      " [nan nan 14.3 '56' '5' 5 2010 56 'S']]\n"
     ]
    }
   ],
   "source": [
    "print(data.values[0:5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "bacc1e4b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   Ozone  Solar.R  Wind Temp C Month  Day  Year  Temp Weather\n",
      "1   41.0    190.0   7.4     67     5    1  2010    67       S\n",
      "2   36.0    118.0   8.0     72     5    2  2010    72       C\n",
      "3   12.0    149.0  12.6     74     5    3  2010    74      PS\n",
      "4   18.0    313.0  11.5     62     5    4  2010    62       S\n",
      "5    NaN      NaN  14.3     56     5    5  2010    56       S\n"
     ]
    }
   ],
   "source": [
    "print(data[0:5])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "122e40bd",
   "metadata": {},
   "source": [
    "# Data structure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "2278d799",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.frame.DataFrame"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f383ee12",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "158 Rows and 9 Columns\n"
     ]
    }
   ],
   "source": [
    "rows, columns = data.shape\n",
    "print(rows,'Rows', 'and',columns,'Columns')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "35e30341",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Ozone      float64\n",
       "Solar.R    float64\n",
       "Wind       float64\n",
       "Temp C      object\n",
       "Month       object\n",
       "Day          int64\n",
       "Year         int64\n",
       "Temp         int64\n",
       "Weather     object\n",
       "dtype: object"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc9b6af2",
   "metadata": {},
   "source": [
    "# Data Type Conversion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "2ec55328",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 158 entries, 1 to 158\n",
      "Data columns (total 9 columns):\n",
      " #   Column   Non-Null Count  Dtype  \n",
      "---  ------   --------------  -----  \n",
      " 0   Ozone    120 non-null    float64\n",
      " 1   Solar.R  151 non-null    float64\n",
      " 2   Wind     158 non-null    float64\n",
      " 3   Temp C   158 non-null    object \n",
      " 4   Month    158 non-null    object \n",
      " 5   Day      158 non-null    int64  \n",
      " 6   Year     158 non-null    int64  \n",
      " 7   Temp     158 non-null    int64  \n",
      " 8   Weather  155 non-null    object \n",
      "dtypes: float64(3), int64(3), object(3)\n",
      "memory usage: 12.3+ KB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "2f7f583d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Ozone</th>\n",
       "      <th>Solar.R</th>\n",
       "      <th>Wind</th>\n",
       "      <th>Temp C</th>\n",
       "      <th>Month</th>\n",
       "      <th>Day</th>\n",
       "      <th>Year</th>\n",
       "      <th>Temp</th>\n",
       "      <th>Weather</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>41.0</td>\n",
       "      <td>190.0</td>\n",
       "      <td>7.4</td>\n",
       "      <td>67</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2010</td>\n",
       "      <td>67</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>36.0</td>\n",
       "      <td>118.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>72</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>2010</td>\n",
       "      <td>72</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12.0</td>\n",
       "      <td>149.0</td>\n",
       "      <td>12.6</td>\n",
       "      <td>74</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>2010</td>\n",
       "      <td>74</td>\n",
       "      <td>PS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>18.0</td>\n",
       "      <td>313.0</td>\n",
       "      <td>11.5</td>\n",
       "      <td>62</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>2010</td>\n",
       "      <td>62</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.3</td>\n",
       "      <td>56</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>56</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>41.0</td>\n",
       "      <td>190.0</td>\n",
       "      <td>7.4</td>\n",
       "      <td>67</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2010</td>\n",
       "      <td>67</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>30.0</td>\n",
       "      <td>193.0</td>\n",
       "      <td>6.9</td>\n",
       "      <td>70</td>\n",
       "      <td>9</td>\n",
       "      <td>26</td>\n",
       "      <td>2010</td>\n",
       "      <td>70</td>\n",
       "      <td>PS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>NaN</td>\n",
       "      <td>145.0</td>\n",
       "      <td>13.2</td>\n",
       "      <td>77</td>\n",
       "      <td>9</td>\n",
       "      <td>27</td>\n",
       "      <td>2010</td>\n",
       "      <td>77</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>14.0</td>\n",
       "      <td>191.0</td>\n",
       "      <td>14.3</td>\n",
       "      <td>75</td>\n",
       "      <td>9</td>\n",
       "      <td>28</td>\n",
       "      <td>2010</td>\n",
       "      <td>75</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>18.0</td>\n",
       "      <td>131.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>76</td>\n",
       "      <td>9</td>\n",
       "      <td>29</td>\n",
       "      <td>2010</td>\n",
       "      <td>76</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>158 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Ozone  Solar.R  Wind Temp C Month  Day  Year  Temp Weather\n",
       "1     41.0    190.0   7.4     67     5    1  2010    67       S\n",
       "2     36.0    118.0   8.0     72     5    2  2010    72       C\n",
       "3     12.0    149.0  12.6     74     5    3  2010    74      PS\n",
       "4     18.0    313.0  11.5     62     5    4  2010    62       S\n",
       "5      NaN      NaN  14.3     56     5    5  2010    56       S\n",
       "..     ...      ...   ...    ...   ...  ...   ...   ...     ...\n",
       "154   41.0    190.0   7.4     67     5    1  2010    67       C\n",
       "155   30.0    193.0   6.9     70     9   26  2010    70      PS\n",
       "156    NaN    145.0  13.2     77     9   27  2010    77       S\n",
       "157   14.0    191.0  14.3     75     9   28  2010    75       S\n",
       "158   18.0    131.0   8.0     76     9   29  2010    76       C\n",
       "\n",
       "[158 rows x 9 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6ba1b204",
   "metadata": {},
   "outputs": [],
   "source": [
    "data['Month'] = pd.to_numeric(data['Month'], errors = 'coerce')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "930bcc08",
   "metadata": {},
   "source": [
    "# coerce will introduce NA values for non numeric data in the columns\n",
    "# if there are values that cannot be changed into numeric it will throw an error therefore the above statement"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "77377236",
   "metadata": {},
   "outputs": [],
   "source": [
    "data['Temp C'] = pd.to_numeric(data['Temp C'], errors = 'coerce')\n",
    "data['Weather'] = data['Weather'].astype('category')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "84e1583b",
   "metadata": {},
   "outputs": [],
   "source": [
    "#data['Wind'] = data['Wind'].astype('int64')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "4c856bab",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 158 entries, 1 to 158\n",
      "Data columns (total 9 columns):\n",
      " #   Column   Non-Null Count  Dtype   \n",
      "---  ------   --------------  -----   \n",
      " 0   Ozone    120 non-null    float64 \n",
      " 1   Solar.R  151 non-null    float64 \n",
      " 2   Wind     158 non-null    float64 \n",
      " 3   Temp C   157 non-null    float64 \n",
      " 4   Month    157 non-null    float64 \n",
      " 5   Day      158 non-null    int64   \n",
      " 6   Year     158 non-null    int64   \n",
      " 7   Temp     158 non-null    int64   \n",
      " 8   Weather  155 non-null    category\n",
      "dtypes: category(1), float64(5), int64(3)\n",
      "memory usage: 11.4 KB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a5336f67",
   "metadata": {},
   "source": [
    "# Remove Duplicates\n",
    "\n",
    "## Count of Duplicated Rows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "017478a0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1, 9)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[data.duplicated()].shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a7f88fae",
   "metadata": {},
   "source": [
    "## print the duplicated rows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "d8ef40a0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Ozone</th>\n",
       "      <th>Solar.R</th>\n",
       "      <th>Wind</th>\n",
       "      <th>Temp C</th>\n",
       "      <th>Month</th>\n",
       "      <th>Day</th>\n",
       "      <th>Year</th>\n",
       "      <th>Temp</th>\n",
       "      <th>Weather</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>14.0</td>\n",
       "      <td>191.0</td>\n",
       "      <td>14.3</td>\n",
       "      <td>75.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>28</td>\n",
       "      <td>2010</td>\n",
       "      <td>75</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Ozone  Solar.R  Wind  Temp C  Month  Day  Year  Temp Weather\n",
       "157   14.0    191.0  14.3    75.0    9.0   28  2010    75       S"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[data.duplicated()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "098df5fd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(158,)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.duplicated().shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "49dc0649",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Ozone</th>\n",
       "      <th>Solar.R</th>\n",
       "      <th>Wind</th>\n",
       "      <th>Temp C</th>\n",
       "      <th>Month</th>\n",
       "      <th>Day</th>\n",
       "      <th>Year</th>\n",
       "      <th>Temp</th>\n",
       "      <th>Weather</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>41.0</td>\n",
       "      <td>190.0</td>\n",
       "      <td>7.4</td>\n",
       "      <td>67.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2010</td>\n",
       "      <td>67</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>36.0</td>\n",
       "      <td>118.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2010</td>\n",
       "      <td>72</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12.0</td>\n",
       "      <td>149.0</td>\n",
       "      <td>12.6</td>\n",
       "      <td>74.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3</td>\n",
       "      <td>2010</td>\n",
       "      <td>74</td>\n",
       "      <td>PS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>18.0</td>\n",
       "      <td>313.0</td>\n",
       "      <td>11.5</td>\n",
       "      <td>62.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4</td>\n",
       "      <td>2010</td>\n",
       "      <td>62</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.3</td>\n",
       "      <td>56.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>56</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>41.0</td>\n",
       "      <td>190.0</td>\n",
       "      <td>7.4</td>\n",
       "      <td>67.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2010</td>\n",
       "      <td>67</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>30.0</td>\n",
       "      <td>193.0</td>\n",
       "      <td>6.9</td>\n",
       "      <td>70.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>26</td>\n",
       "      <td>2010</td>\n",
       "      <td>70</td>\n",
       "      <td>PS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>NaN</td>\n",
       "      <td>145.0</td>\n",
       "      <td>13.2</td>\n",
       "      <td>77.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>27</td>\n",
       "      <td>2010</td>\n",
       "      <td>77</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>14.0</td>\n",
       "      <td>191.0</td>\n",
       "      <td>14.3</td>\n",
       "      <td>75.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>28</td>\n",
       "      <td>2010</td>\n",
       "      <td>75</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>18.0</td>\n",
       "      <td>131.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>29</td>\n",
       "      <td>2010</td>\n",
       "      <td>76</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>158 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Ozone  Solar.R  Wind  Temp C  Month  Day  Year  Temp Weather\n",
       "1     41.0    190.0   7.4    67.0    5.0    1  2010    67       S\n",
       "2     36.0    118.0   8.0    72.0    5.0    2  2010    72       C\n",
       "3     12.0    149.0  12.6    74.0    5.0    3  2010    74      PS\n",
       "4     18.0    313.0  11.5    62.0    5.0    4  2010    62       S\n",
       "5      NaN      NaN  14.3    56.0    5.0    5  2010    56       S\n",
       "..     ...      ...   ...     ...    ...  ...   ...   ...     ...\n",
       "154   41.0    190.0   7.4    67.0    5.0    1  2010    67       C\n",
       "155   30.0    193.0   6.9    70.0    9.0   26  2010    70      PS\n",
       "156    NaN    145.0  13.2    77.0    9.0   27  2010    77       S\n",
       "157   14.0    191.0  14.3    75.0    9.0   28  2010    75       S\n",
       "158   18.0    131.0   8.0    76.0    9.0   29  2010    76       C\n",
       "\n",
       "[158 rows x 9 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "a154041b",
   "metadata": {},
   "outputs": [],
   "source": [
    "data1 = data.drop_duplicates()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "ff6f5d9d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(157, 9)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data1.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6fd55724",
   "metadata": {},
   "source": [
    "# Drop Columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "eefdcae2",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>Ozone</th>\n",
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       "      <td>3</td>\n",
       "      <td>2010</td>\n",
       "      <td>74</td>\n",
       "      <td>PS</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>18.0</td>\n",
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       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>56</td>\n",
       "      <td>S</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
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       "      <td>190.0</td>\n",
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       "      <td>1</td>\n",
       "      <td>2010</td>\n",
       "      <td>67</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>30.0</td>\n",
       "      <td>193.0</td>\n",
       "      <td>6.9</td>\n",
       "      <td>9.0</td>\n",
       "      <td>26</td>\n",
       "      <td>2010</td>\n",
       "      <td>70</td>\n",
       "      <td>PS</td>\n",
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       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>NaN</td>\n",
       "      <td>145.0</td>\n",
       "      <td>13.2</td>\n",
       "      <td>9.0</td>\n",
       "      <td>27</td>\n",
       "      <td>2010</td>\n",
       "      <td>77</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>18.0</td>\n",
       "      <td>131.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>29</td>\n",
       "      <td>2010</td>\n",
       "      <td>76</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>157 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Ozone  Solar.R  Wind  Month  Day  Year  Temp Weather\n",
       "1     41.0    190.0   7.4    5.0    1  2010    67       S\n",
       "2     36.0    118.0   8.0    5.0    2  2010    72       C\n",
       "3     12.0    149.0  12.6    5.0    3  2010    74      PS\n",
       "4     18.0    313.0  11.5    5.0    4  2010    62       S\n",
       "5      NaN      NaN  14.3    5.0    5  2010    56       S\n",
       "..     ...      ...   ...    ...  ...   ...   ...     ...\n",
       "153   20.0    223.0  11.5    9.0   30  2010    68       S\n",
       "154   41.0    190.0   7.4    5.0    1  2010    67       C\n",
       "155   30.0    193.0   6.9    9.0   26  2010    70      PS\n",
       "156    NaN    145.0  13.2    9.0   27  2010    77       S\n",
       "158   18.0    131.0   8.0    9.0   29  2010    76       C\n",
       "\n",
       "[157 rows x 8 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data2 = data1.drop('Temp C', axis =1)\n",
    "data2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6f525d57",
   "metadata": {},
   "source": [
    "# Rename the weird columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "124d7413",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>S</td>\n",
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      ],
      "text/plain": [
       "     Ozone  Solar  Wind  Month  Day  Year  Temp Weather\n",
       "1     41.0  190.0   7.4    5.0    1  2010    67       S\n",
       "2     36.0  118.0   8.0    5.0    2  2010    72       C\n",
       "3     12.0  149.0  12.6    5.0    3  2010    74      PS\n",
       "4     18.0  313.0  11.5    5.0    4  2010    62       S\n",
       "5      NaN    NaN  14.3    5.0    5  2010    56       S\n",
       "..     ...    ...   ...    ...  ...   ...   ...     ...\n",
       "153   20.0  223.0  11.5    9.0   30  2010    68       S\n",
       "154   41.0  190.0   7.4    5.0    1  2010    67       C\n",
       "155   30.0  193.0   6.9    9.0   26  2010    70      PS\n",
       "156    NaN  145.0  13.2    9.0   27  2010    77       S\n",
       "158   18.0  131.0   8.0    9.0   29  2010    76       C\n",
       "\n",
       "[157 rows x 8 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data3 = data2.rename({'Solar.R':'Solar'}, axis = 1)\n",
    "data3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "5798cbc6",
   "metadata": {},
   "outputs": [
    {
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       "      <td>287.0</td>\n",
       "      <td>9.7</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2010</td>\n",
       "      <td>74</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>NaN</td>\n",
       "      <td>242.0</td>\n",
       "      <td>16.1</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3</td>\n",
       "      <td>2010</td>\n",
       "      <td>67</td>\n",
       "      <td>PS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>NaN</td>\n",
       "      <td>186.0</td>\n",
       "      <td>9.2</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4</td>\n",
       "      <td>2010</td>\n",
       "      <td>84</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>NaN</td>\n",
       "      <td>220.0</td>\n",
       "      <td>8.6</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>85</td>\n",
       "      <td>PS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>NaN</td>\n",
       "      <td>264.0</td>\n",
       "      <td>14.3</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6</td>\n",
       "      <td>2010</td>\n",
       "      <td>79</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>29.0</td>\n",
       "      <td>127.0</td>\n",
       "      <td>9.7</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7</td>\n",
       "      <td>2010</td>\n",
       "      <td>82</td>\n",
       "      <td>PS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>NaN</td>\n",
       "      <td>273.0</td>\n",
       "      <td>6.9</td>\n",
       "      <td>6.0</td>\n",
       "      <td>8</td>\n",
       "      <td>2010</td>\n",
       "      <td>87</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>71.0</td>\n",
       "      <td>291.0</td>\n",
       "      <td>13.8</td>\n",
       "      <td>6.0</td>\n",
       "      <td>9</td>\n",
       "      <td>2010</td>\n",
       "      <td>90</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>39.0</td>\n",
       "      <td>323.0</td>\n",
       "      <td>11.5</td>\n",
       "      <td>6.0</td>\n",
       "      <td>10</td>\n",
       "      <td>2010</td>\n",
       "      <td>87</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>NaN</td>\n",
       "      <td>259.0</td>\n",
       "      <td>10.9</td>\n",
       "      <td>6.0</td>\n",
       "      <td>11</td>\n",
       "      <td>2010</td>\n",
       "      <td>93</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>NaN</td>\n",
       "      <td>250.0</td>\n",
       "      <td>9.2</td>\n",
       "      <td>6.0</td>\n",
       "      <td>12</td>\n",
       "      <td>2010</td>\n",
       "      <td>92</td>\n",
       "      <td>PS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>23.0</td>\n",
       "      <td>148.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>13</td>\n",
       "      <td>2010</td>\n",
       "      <td>82</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>NaN</td>\n",
       "      <td>332.0</td>\n",
       "      <td>13.8</td>\n",
       "      <td>6.0</td>\n",
       "      <td>14</td>\n",
       "      <td>2010</td>\n",
       "      <td>80</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>NaN</td>\n",
       "      <td>322.0</td>\n",
       "      <td>11.5</td>\n",
       "      <td>6.0</td>\n",
       "      <td>15</td>\n",
       "      <td>2010</td>\n",
       "      <td>79</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>21.0</td>\n",
       "      <td>191.0</td>\n",
       "      <td>14.9</td>\n",
       "      <td>6.0</td>\n",
       "      <td>16</td>\n",
       "      <td>2010</td>\n",
       "      <td>77</td>\n",
       "      <td>PS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>37.0</td>\n",
       "      <td>284.0</td>\n",
       "      <td>20.7</td>\n",
       "      <td>6.0</td>\n",
       "      <td>17</td>\n",
       "      <td>2010</td>\n",
       "      <td>72</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>20.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>9.2</td>\n",
       "      <td>6.0</td>\n",
       "      <td>18</td>\n",
       "      <td>2010</td>\n",
       "      <td>65</td>\n",
       "      <td>PS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>12.0</td>\n",
       "      <td>120.0</td>\n",
       "      <td>11.5</td>\n",
       "      <td>6.0</td>\n",
       "      <td>19</td>\n",
       "      <td>2010</td>\n",
       "      <td>73</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>13.0</td>\n",
       "      <td>137.0</td>\n",
       "      <td>10.3</td>\n",
       "      <td>6.0</td>\n",
       "      <td>20</td>\n",
       "      <td>2010</td>\n",
       "      <td>76</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>NaN</td>\n",
       "      <td>150.0</td>\n",
       "      <td>6.3</td>\n",
       "      <td>6.0</td>\n",
       "      <td>21</td>\n",
       "      <td>2010</td>\n",
       "      <td>77</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>NaN</td>\n",
       "      <td>59.0</td>\n",
       "      <td>1.7</td>\n",
       "      <td>6.0</td>\n",
       "      <td>22</td>\n",
       "      <td>2010</td>\n",
       "      <td>76</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>NaN</td>\n",
       "      <td>91.0</td>\n",
       "      <td>4.6</td>\n",
       "      <td>6.0</td>\n",
       "      <td>23</td>\n",
       "      <td>2010</td>\n",
       "      <td>76</td>\n",
       "      <td>PS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>NaN</td>\n",
       "      <td>250.0</td>\n",
       "      <td>6.3</td>\n",
       "      <td>6.0</td>\n",
       "      <td>24</td>\n",
       "      <td>2010</td>\n",
       "      <td>76</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>NaN</td>\n",
       "      <td>135.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>25</td>\n",
       "      <td>2010</td>\n",
       "      <td>75</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>NaN</td>\n",
       "      <td>127.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>26</td>\n",
       "      <td>2010</td>\n",
       "      <td>78</td>\n",
       "      <td>PS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>NaN</td>\n",
       "      <td>47.0</td>\n",
       "      <td>10.3</td>\n",
       "      <td>6.0</td>\n",
       "      <td>27</td>\n",
       "      <td>2010</td>\n",
       "      <td>73</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>NaN</td>\n",
       "      <td>98.0</td>\n",
       "      <td>11.5</td>\n",
       "      <td>6.0</td>\n",
       "      <td>28</td>\n",
       "      <td>2010</td>\n",
       "      <td>80</td>\n",
       "      <td>PS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>NaN</td>\n",
       "      <td>31.0</td>\n",
       "      <td>14.9</td>\n",
       "      <td>6.0</td>\n",
       "      <td>29</td>\n",
       "      <td>2010</td>\n",
       "      <td>77</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>NaN</td>\n",
       "      <td>138.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>30</td>\n",
       "      <td>2010</td>\n",
       "      <td>83</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Ozone  Solar  Wind  Month  Day  Year  Temp Weather\n",
       "32    NaN  286.0   8.6    6.0    1  2010    78       S\n",
       "33    NaN  287.0   9.7    6.0    2  2010    74       C\n",
       "34    NaN  242.0  16.1    6.0    3  2010    67      PS\n",
       "35    NaN  186.0   9.2    6.0    4  2010    84       C\n",
       "36    NaN  220.0   8.6    6.0    5  2010    85      PS\n",
       "37    NaN  264.0  14.3    6.0    6  2010    79       C\n",
       "38   29.0  127.0   9.7    6.0    7  2010    82      PS\n",
       "39    NaN  273.0   6.9    6.0    8  2010    87       S\n",
       "40   71.0  291.0  13.8    6.0    9  2010    90       S\n",
       "41   39.0  323.0  11.5    6.0   10  2010    87       S\n",
       "42    NaN  259.0  10.9    6.0   11  2010    93       C\n",
       "43    NaN  250.0   9.2    6.0   12  2010    92      PS\n",
       "44   23.0  148.0   8.0    6.0   13  2010    82       S\n",
       "45    NaN  332.0  13.8    6.0   14  2010    80       S\n",
       "46    NaN  322.0  11.5    6.0   15  2010    79       C\n",
       "47   21.0  191.0  14.9    6.0   16  2010    77      PS\n",
       "48   37.0  284.0  20.7    6.0   17  2010    72       C\n",
       "49   20.0   37.0   9.2    6.0   18  2010    65      PS\n",
       "50   12.0  120.0  11.5    6.0   19  2010    73       S\n",
       "51   13.0  137.0  10.3    6.0   20  2010    76       S\n",
       "52    NaN  150.0   6.3    6.0   21  2010    77       S\n",
       "53    NaN   59.0   1.7    6.0   22  2010    76       C\n",
       "54    NaN   91.0   4.6    6.0   23  2010    76      PS\n",
       "55    NaN  250.0   6.3    6.0   24  2010    76       S\n",
       "56    NaN  135.0   8.0    6.0   25  2010    75       C\n",
       "57    NaN  127.0   8.0    6.0   26  2010    78      PS\n",
       "58    NaN   47.0  10.3    6.0   27  2010    73       C\n",
       "59    NaN   98.0  11.5    6.0   28  2010    80      PS\n",
       "60    NaN   31.0  14.9    6.0   29  2010    77       S\n",
       "61    NaN  138.0   8.0    6.0   30  2010    83       S"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data3.loc[data3['Month'] == 6]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3169870a",
   "metadata": {},
   "source": [
    "# Outlier Detection\n",
    "\n",
    "## Plot histogram of Ozone"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "eb01c9e7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "plt.subplots(figsize = (16,9))\n",
    "plt.subplot(221)\n",
    "plt.hist(data3['Ozone'], bins =10)\n",
    "plt.title('Ozone')\n",
    "plt.subplot(222)\n",
    "plt.hist(data3['Solar'], bins =10)\n",
    "plt.title('Solar')\n",
    "plt.subplot(223)\n",
    "plt.hist(data3['Wind'], bins =10)\n",
    "plt.title('Wind')\n",
    "plt.subplot(224)\n",
    "plt.hist(data3['Month'], bins = 10)\n",
    "plt.title('Month')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "6838f77c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "plt.subplots(figsize = (16,9))\n",
    "plt.subplot(221)\n",
    "data3['Day'].hist()\n",
    "plt.title('Day')\n",
    "plt.subplot(222)\n",
    "data3['Year'].hist()\n",
    "plt.title('Year')\n",
    "plt.subplot(223)\n",
    "data3['Temp'].hist()\n",
    "plt.title('Temp')\n",
    "plt.subplot(224)\n",
    "data3['Weather'].hist()\n",
    "plt.title('Weather')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "2ac926e3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "data3['Ozone'].hist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "1a46fb3c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "data3['Solar'].hist()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "22047396",
   "metadata": {},
   "source": [
    "## Box plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "cdfa87a3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'whiskers': [<matplotlib.lines.Line2D at 0x17833f64dc0>,\n",
       "  <matplotlib.lines.Line2D at 0x17833f70190>],\n",
       " 'caps': [<matplotlib.lines.Line2D at 0x17833f70520>,\n",
       "  <matplotlib.lines.Line2D at 0x17833f708b0>],\n",
       " 'boxes': [<matplotlib.lines.Line2D at 0x17833f64a30>],\n",
       " 'medians': [<matplotlib.lines.Line2D at 0x17833f70c40>],\n",
       " 'fliers': [<matplotlib.lines.Line2D at 0x17833f70fd0>],\n",
       " 'means': []}"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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pQYa7tIQk+5IcSbKw3r1Iq2W4S0u7HbhuvZuQ+mG4S0uoqgeBo+vdh9QPw12SGmS4S1KDDHdJapDhLkkNMtylJSSZAb4EvDnJwSRT692TtFLeoSpJDfLMXZIaZLhLUoMMd0lqkOEuSQ0y3CWpQYa7JDXIcJekBhnuktSg/wcI2NDUToxwqwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "data_box_plot = data3.dropna()\n",
    "data1_box_plot = data_box_plot.Ozone\n",
    "plt.boxplot(data1_box_plot)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "c713180b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'whiskers': [<matplotlib.lines.Line2D at 0x20f6db83be0>,\n",
       "  <matplotlib.lines.Line2D at 0x20f6db83ee0>],\n",
       " 'caps': [<matplotlib.lines.Line2D at 0x20f6db992b0>,\n",
       "  <matplotlib.lines.Line2D at 0x20f6db99640>],\n",
       " 'boxes': [<matplotlib.lines.Line2D at 0x20f6db83790>],\n",
       " 'medians': [<matplotlib.lines.Line2D at 0x20f6db999d0>],\n",
       " 'fliers': [<matplotlib.lines.Line2D at 0x20f6db99d60>],\n",
       " 'means': []}"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Y+MNazyEth3GXpAYZd0lqkHGXpAYZd0lqkHGXFpHkEeCnwF8nmUty21rPJI3LT6hKUoN85y5JDTLuktQg4y5JDTLuktQg4y5JDTLuktQg4y5JDTLuktSg/wW/5PrVcw7UPAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "data2_box_plot = data3.dropna()\n",
    "data3_box_plot = data2_box_plot.Solar\n",
    "plt.boxplot(data3_box_plot)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "f7c3696a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "data_box_plot.boxplot(column = ['Ozone'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1579819e",
   "metadata": {},
   "source": [
    "## Extracting Outliers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "f3394250",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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pQYa7tIQk+5IcSbKw3r1Iq2W4S0u7HbhuvZuQ+mG4S0uoqgeBo+vdh9QPw12SGmS4S1KDDHdJapDhLkkNMtylJSSZAb4EvDnJwSRT692TtFLeoSpJDfLMXZIaZLhLUoMMd0lqkOEuSQ0y3CWpQYa7JDXIcJekBhnuktSg/wcI2NDUToxwqwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "box = plt.boxplot(data1_box_plot)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "e25dc1f8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'whiskers': [<matplotlib.lines.Line2D at 0x17834170520>,\n",
       "  <matplotlib.lines.Line2D at 0x178341708b0>],\n",
       " 'caps': [<matplotlib.lines.Line2D at 0x17834170c40>,\n",
       "  <matplotlib.lines.Line2D at 0x17834170fd0>],\n",
       " 'boxes': [<matplotlib.lines.Line2D at 0x178341701f0>],\n",
       " 'medians': [<matplotlib.lines.Line2D at 0x1783417b3a0>],\n",
       " 'fliers': [<matplotlib.lines.Line2D at 0x1783417b730>],\n",
       " 'means': []}"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "box"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e3af0a8",
   "metadata": {},
   "source": [
    "## Fliers are Outliers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "3856631e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "list"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(box['fliers'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "6458248a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Line2D(_line6)\n",
      "[135. 168.]\n"
     ]
    }
   ],
   "source": [
    "for elem in box['fliers']:\n",
    "    print(elem)\n",
    "    print(elem.get_ydata())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "6fea9c53",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[array([135., 168.])]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[item.get_ydata() for item in box['fliers']]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "79a5e8a2",
   "metadata": {},
   "source": [
    "## To get Whiskers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "050b4315",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Line2D(_line1)\n",
      "[18.  1.]\n",
      "Line2D(_line2)\n",
      "[ 62. 122.]\n"
     ]
    }
   ],
   "source": [
    "for elem in box['whiskers']:\n",
    "    print(elem)\n",
    "    print(elem.get_ydata())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "5f77362e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[array([18.,  1.]), array([ 62., 122.])]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[item.get_ydata() for item in box['whiskers']]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3722e3af",
   "metadata": {},
   "source": [
    "## Descriptive Stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "5284ac47",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    119.000000\n",
       "mean      41.815126\n",
       "std       32.659249\n",
       "min        1.000000\n",
       "25%       18.000000\n",
       "50%       31.000000\n",
       "75%       62.000000\n",
       "max      168.000000\n",
       "Name: Ozone, dtype: float64"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data3['Ozone'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "503f0b10",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Ozone</th>\n",
       "      <th>Solar</th>\n",
       "      <th>Wind</th>\n",
       "      <th>Month</th>\n",
       "      <th>Day</th>\n",
       "      <th>Year</th>\n",
       "      <th>Temp</th>\n",
       "      <th>Weather</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>41.0</td>\n",
       "      <td>190.0</td>\n",
       "      <td>7.4</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2010</td>\n",
       "      <td>67</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>36.0</td>\n",
       "      <td>118.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2010</td>\n",
       "      <td>72</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12.0</td>\n",
       "      <td>149.0</td>\n",
       "      <td>12.6</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3</td>\n",
       "      <td>2010</td>\n",
       "      <td>74</td>\n",
       "      <td>PS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>18.0</td>\n",
       "      <td>313.0</td>\n",
       "      <td>11.5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4</td>\n",
       "      <td>2010</td>\n",
       "      <td>62</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.3</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>56</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>20.0</td>\n",
       "      <td>223.0</td>\n",
       "      <td>11.5</td>\n",
       "      <td>9.0</td>\n",
       "      <td>30</td>\n",
       "      <td>2010</td>\n",
       "      <td>68</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>41.0</td>\n",
       "      <td>190.0</td>\n",
       "      <td>7.4</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2010</td>\n",
       "      <td>67</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>30.0</td>\n",
       "      <td>193.0</td>\n",
       "      <td>6.9</td>\n",
       "      <td>9.0</td>\n",
       "      <td>26</td>\n",
       "      <td>2010</td>\n",
       "      <td>70</td>\n",
       "      <td>PS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>NaN</td>\n",
       "      <td>145.0</td>\n",
       "      <td>13.2</td>\n",
       "      <td>9.0</td>\n",
       "      <td>27</td>\n",
       "      <td>2010</td>\n",
       "      <td>77</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>18.0</td>\n",
       "      <td>131.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>29</td>\n",
       "      <td>2010</td>\n",
       "      <td>76</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>157 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Ozone  Solar  Wind  Month  Day  Year  Temp Weather\n",
       "1     41.0  190.0   7.4    5.0    1  2010    67       S\n",
       "2     36.0  118.0   8.0    5.0    2  2010    72       C\n",
       "3     12.0  149.0  12.6    5.0    3  2010    74      PS\n",
       "4     18.0  313.0  11.5    5.0    4  2010    62       S\n",
       "5      NaN    NaN  14.3    5.0    5  2010    56       S\n",
       "..     ...    ...   ...    ...  ...   ...   ...     ...\n",
       "153   20.0  223.0  11.5    9.0   30  2010    68       S\n",
       "154   41.0  190.0   7.4    5.0    1  2010    67       C\n",
       "155   30.0  193.0   6.9    9.0   26  2010    70      PS\n",
       "156    NaN  145.0  13.2    9.0   27  2010    77       S\n",
       "158   18.0  131.0   8.0    9.0   29  2010    76       C\n",
       "\n",
       "[157 rows x 8 columns]"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data3"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aea808ce",
   "metadata": {},
   "source": [
    "# Check for Balaced or Imbalanced Data in Categorical data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ef801749",
   "metadata": {},
   "source": [
    "## Bar Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "656ce8b0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data['Weather'].value_counts().plot.bar()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "916b181d",
   "metadata": {},
   "source": [
    "# Missing Values and Imputation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "94a1a14f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (16,9))\n",
    "plt.xticks(fontsize = 14)\n",
    "cols= data3.columns\n",
    "colors = ['#000000','#7FFF00']\n",
    "sns.heatmap(data3[cols].isnull(), cmap = sns.color_palette(colors))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "1550e19d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Ozone      38\n",
       "Solar       7\n",
       "Wind        0\n",
       "Month       1\n",
       "Day         0\n",
       "Year        0\n",
       "Temp        0\n",
       "Weather     3\n",
       "dtype: int64"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data3.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "de43468f",
   "metadata": {},
   "source": [
    "## Mean Imputation "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "63a7b9f9",
   "metadata": {},
   "outputs": [],
   "source": [
    "mean  = data3['Ozone'].mean()\n",
    "mean_solar = data3['Solar'].mean()\n",
    "mean_month = data3['Month'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "c38c3a92",
   "metadata": {},
   "outputs": [],
   "source": [
    "data3['Ozone'] = data3['Ozone'].fillna(mean)\n",
    "data3['Solar'] = data3['Solar'].fillna(mean_solar)\n",
    "data3['Month'] = data3['Month'].fillna(mean_month)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "958e94b3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Ozone</th>\n",
       "      <th>Solar</th>\n",
       "      <th>Wind</th>\n",
       "      <th>Month</th>\n",
       "      <th>Day</th>\n",
       "      <th>Year</th>\n",
       "      <th>Temp</th>\n",
       "      <th>Weather</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>41.000000</td>\n",
       "      <td>190.000000</td>\n",
       "      <td>7.4</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2010</td>\n",
       "      <td>67</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>36.000000</td>\n",
       "      <td>118.000000</td>\n",
       "      <td>8.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2010</td>\n",
       "      <td>72</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12.000000</td>\n",
       "      <td>149.000000</td>\n",
       "      <td>12.6</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3</td>\n",
       "      <td>2010</td>\n",
       "      <td>74</td>\n",
       "      <td>PS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>18.000000</td>\n",
       "      <td>313.000000</td>\n",
       "      <td>11.5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4</td>\n",
       "      <td>2010</td>\n",
       "      <td>62</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>41.815126</td>\n",
       "      <td>185.366667</td>\n",
       "      <td>14.3</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>56</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>20.000000</td>\n",
       "      <td>223.000000</td>\n",
       "      <td>11.5</td>\n",
       "      <td>9.0</td>\n",
       "      <td>30</td>\n",
       "      <td>2010</td>\n",
       "      <td>68</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>41.000000</td>\n",
       "      <td>190.000000</td>\n",
       "      <td>7.4</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2010</td>\n",
       "      <td>67</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>30.000000</td>\n",
       "      <td>193.000000</td>\n",
       "      <td>6.9</td>\n",
       "      <td>9.0</td>\n",
       "      <td>26</td>\n",
       "      <td>2010</td>\n",
       "      <td>70</td>\n",
       "      <td>PS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>41.815126</td>\n",
       "      <td>145.000000</td>\n",
       "      <td>13.2</td>\n",
       "      <td>9.0</td>\n",
       "      <td>27</td>\n",
       "      <td>2010</td>\n",
       "      <td>77</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>18.000000</td>\n",
       "      <td>131.000000</td>\n",
       "      <td>8.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>29</td>\n",
       "      <td>2010</td>\n",
       "      <td>76</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>157 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Ozone       Solar  Wind  Month  Day  Year  Temp Weather\n",
       "1    41.000000  190.000000   7.4    5.0    1  2010    67       S\n",
       "2    36.000000  118.000000   8.0    5.0    2  2010    72       C\n",
       "3    12.000000  149.000000  12.6    5.0    3  2010    74      PS\n",
       "4    18.000000  313.000000  11.5    5.0    4  2010    62       S\n",
       "5    41.815126  185.366667  14.3    5.0    5  2010    56       S\n",
       "..         ...         ...   ...    ...  ...   ...   ...     ...\n",
       "153  20.000000  223.000000  11.5    9.0   30  2010    68       S\n",
       "154  41.000000  190.000000   7.4    5.0    1  2010    67       C\n",
       "155  30.000000  193.000000   6.9    9.0   26  2010    70      PS\n",
       "156  41.815126  145.000000  13.2    9.0   27  2010    77       S\n",
       "158  18.000000  131.000000   8.0    9.0   29  2010    76       C\n",
       "\n",
       "[157 rows x 8 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "afb3d77a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Ozone      0\n",
       "Solar      0\n",
       "Wind       0\n",
       "Month      0\n",
       "Day        0\n",
       "Year       0\n",
       "Temp       0\n",
       "Weather    3\n",
       "dtype: int64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data3.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a439fbfe",
   "metadata": {},
   "source": [
    "# Null values Imputation for categorical data/values\n",
    "## Get the object values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "55f88a72",
   "metadata": {},
   "outputs": [],
   "source": [
    "test = data3[\"Weather\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "b16a6713",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1       S\n",
       "2       C\n",
       "3      PS\n",
       "4       S\n",
       "5       S\n",
       "       ..\n",
       "153     S\n",
       "154     C\n",
       "155    PS\n",
       "156     S\n",
       "158     C\n",
       "Name: Weather, Length: 157, dtype: category\n",
       "Categories (3, object): ['C', 'PS', 'S']"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "8b6e65af",
   "metadata": {},
   "outputs": [],
   "source": [
    "weather_column = data3[['Weather']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "24bee178",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Weather</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>PS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>PS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>157 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Weather\n",
       "1         S\n",
       "2         C\n",
       "3        PS\n",
       "4         S\n",
       "5         S\n",
       "..      ...\n",
       "153       S\n",
       "154       C\n",
       "155      PS\n",
       "156       S\n",
       "158       C\n",
       "\n",
       "[157 rows x 1 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weather_column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "a6e2c9d4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weather_column.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "cf22e1cd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Weather</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Weather\n",
       "0       S"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weather_column.mode()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "ac5b8e04",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Weather    S\n",
       "Name: 0, dtype: category\n",
       "Categories (3, object): ['C', 'PS', 'S']"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weather_column.mode().iloc[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8edd25fd",
   "metadata": {},
   "source": [
    "### Missing value imputation for categorical value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "6b0ba242",
   "metadata": {},
   "outputs": [],
   "source": [
    "weather_column=weather_column.fillna(weather_column.mode().iloc[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "6c3cd05e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Weather    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weather_column.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "7865b8cd",
   "metadata": {},
   "outputs": [],
   "source": [
    "data4 = data3.drop(['Weather'], axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "85e588a7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Ozone</th>\n",
       "      <th>Solar</th>\n",
       "      <th>Wind</th>\n",
       "      <th>Month</th>\n",
       "      <th>Day</th>\n",
       "      <th>Year</th>\n",
       "      <th>Temp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>41.000000</td>\n",
       "      <td>190.0</td>\n",
       "      <td>7.4</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2010</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>36.000000</td>\n",
       "      <td>118.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2010</td>\n",
       "      <td>72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12.000000</td>\n",
       "      <td>149.0</td>\n",
       "      <td>12.6</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3</td>\n",
       "      <td>2010</td>\n",
       "      <td>74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>18.000000</td>\n",
       "      <td>313.0</td>\n",
       "      <td>11.5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4</td>\n",
       "      <td>2010</td>\n",
       "      <td>62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>41.815126</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.3</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>20.000000</td>\n",
       "      <td>223.0</td>\n",
       "      <td>11.5</td>\n",
       "      <td>9.0</td>\n",
       "      <td>30</td>\n",
       "      <td>2010</td>\n",
       "      <td>68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>41.000000</td>\n",
       "      <td>190.0</td>\n",
       "      <td>7.4</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2010</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>30.000000</td>\n",
       "      <td>193.0</td>\n",
       "      <td>6.9</td>\n",
       "      <td>9.0</td>\n",
       "      <td>26</td>\n",
       "      <td>2010</td>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>41.815126</td>\n",
       "      <td>145.0</td>\n",
       "      <td>13.2</td>\n",
       "      <td>9.0</td>\n",
       "      <td>27</td>\n",
       "      <td>2010</td>\n",
       "      <td>77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>18.000000</td>\n",
       "      <td>131.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>29</td>\n",
       "      <td>2010</td>\n",
       "      <td>76</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>157 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Ozone  Solar  Wind  Month  Day  Year  Temp\n",
       "1    41.000000  190.0   7.4    5.0    1  2010    67\n",
       "2    36.000000  118.0   8.0    5.0    2  2010    72\n",
       "3    12.000000  149.0  12.6    5.0    3  2010    74\n",
       "4    18.000000  313.0  11.5    5.0    4  2010    62\n",
       "5    41.815126    NaN  14.3    5.0    5  2010    56\n",
       "..         ...    ...   ...    ...  ...   ...   ...\n",
       "153  20.000000  223.0  11.5    9.0   30  2010    68\n",
       "154  41.000000  190.0   7.4    5.0    1  2010    67\n",
       "155  30.000000  193.0   6.9    9.0   26  2010    70\n",
       "156  41.815126  145.0  13.2    9.0   27  2010    77\n",
       "158  18.000000  131.0   8.0    9.0   29  2010    76\n",
       "\n",
       "[157 rows x 7 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data4"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9368a752",
   "metadata": {},
   "source": [
    "# Join the data set with imputed object dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "0e20f09a",
   "metadata": {},
   "outputs": [],
   "source": [
    "data4 = pd.concat([data4, weather_column],axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "af851658",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Ozone</th>\n",
       "      <th>Solar</th>\n",
       "      <th>Wind</th>\n",
       "      <th>Month</th>\n",
       "      <th>Day</th>\n",
       "      <th>Year</th>\n",
       "      <th>Temp</th>\n",
       "      <th>Weather</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>41.000000</td>\n",
       "      <td>190.0</td>\n",
       "      <td>7.4</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2010</td>\n",
       "      <td>67</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>36.000000</td>\n",
       "      <td>118.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2010</td>\n",
       "      <td>72</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12.000000</td>\n",
       "      <td>149.0</td>\n",
       "      <td>12.6</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3</td>\n",
       "      <td>2010</td>\n",
       "      <td>74</td>\n",
       "      <td>PS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>18.000000</td>\n",
       "      <td>313.0</td>\n",
       "      <td>11.5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4</td>\n",
       "      <td>2010</td>\n",
       "      <td>62</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>41.815126</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.3</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>56</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>20.000000</td>\n",
       "      <td>223.0</td>\n",
       "      <td>11.5</td>\n",
       "      <td>9.0</td>\n",
       "      <td>30</td>\n",
       "      <td>2010</td>\n",
       "      <td>68</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>41.000000</td>\n",
       "      <td>190.0</td>\n",
       "      <td>7.4</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2010</td>\n",
       "      <td>67</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>30.000000</td>\n",
       "      <td>193.0</td>\n",
       "      <td>6.9</td>\n",
       "      <td>9.0</td>\n",
       "      <td>26</td>\n",
       "      <td>2010</td>\n",
       "      <td>70</td>\n",
       "      <td>PS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>41.815126</td>\n",
       "      <td>145.0</td>\n",
       "      <td>13.2</td>\n",
       "      <td>9.0</td>\n",
       "      <td>27</td>\n",
       "      <td>2010</td>\n",
       "      <td>77</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>18.000000</td>\n",
       "      <td>131.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>29</td>\n",
       "      <td>2010</td>\n",
       "      <td>76</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>157 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Ozone  Solar  Wind  Month  Day  Year  Temp Weather\n",
       "1    41.000000  190.0   7.4    5.0    1  2010    67       S\n",
       "2    36.000000  118.0   8.0    5.0    2  2010    72       C\n",
       "3    12.000000  149.0  12.6    5.0    3  2010    74      PS\n",
       "4    18.000000  313.0  11.5    5.0    4  2010    62       S\n",
       "5    41.815126    NaN  14.3    5.0    5  2010    56       S\n",
       "..         ...    ...   ...    ...  ...   ...   ...     ...\n",
       "153  20.000000  223.0  11.5    9.0   30  2010    68       S\n",
       "154  41.000000  190.0   7.4    5.0    1  2010    67       C\n",
       "155  30.000000  193.0   6.9    9.0   26  2010    70      PS\n",
       "156  41.815126  145.0  13.2    9.0   27  2010    77       S\n",
       "158  18.000000  131.0   8.0    9.0   29  2010    76       C\n",
       "\n",
       "[157 rows x 8 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "7c626153",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Ozone      0\n",
       "Solar      7\n",
       "Wind       0\n",
       "Month      1\n",
       "Day        0\n",
       "Year       0\n",
       "Temp       0\n",
       "Weather    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data4.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "794d9a0f",
   "metadata": {},
   "source": [
    "# Scatter plot and Correlation Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "f86b94ca",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1260x1260 with 56 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "sns.pairplot(data4)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "3306ddb5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Ozone</th>\n",
       "      <th>Solar</th>\n",
       "      <th>Wind</th>\n",
       "      <th>Month</th>\n",
       "      <th>Day</th>\n",
       "      <th>Year</th>\n",
       "      <th>Temp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Ozone</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.308687</td>\n",
       "      <td>-0.520004</td>\n",
       "      <td>0.132860</td>\n",
       "      <td>-0.021916</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.606500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Solar</th>\n",
       "      <td>0.308687</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.057407</td>\n",
       "      <td>-0.094012</td>\n",
       "      <td>-0.155663</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.273558</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wind</th>\n",
       "      <td>-0.520004</td>\n",
       "      <td>-0.057407</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.166216</td>\n",
       "      <td>0.029900</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.441228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Month</th>\n",
       "      <td>0.132860</td>\n",
       "      <td>-0.094012</td>\n",
       "      <td>-0.166216</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.050055</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.398516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Day</th>\n",
       "      <td>-0.021916</td>\n",
       "      <td>-0.155663</td>\n",
       "      <td>0.029900</td>\n",
       "      <td>0.050055</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.122787</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Temp</th>\n",
       "      <td>0.606500</td>\n",
       "      <td>0.273558</td>\n",
       "      <td>-0.441228</td>\n",
       "      <td>0.398516</td>\n",
       "      <td>-0.122787</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Ozone     Solar      Wind     Month       Day  Year      Temp\n",
       "Ozone  1.000000  0.308687 -0.520004  0.132860 -0.021916   NaN  0.606500\n",
       "Solar  0.308687  1.000000 -0.057407 -0.094012 -0.155663   NaN  0.273558\n",
       "Wind  -0.520004 -0.057407  1.000000 -0.166216  0.029900   NaN -0.441228\n",
       "Month  0.132860 -0.094012 -0.166216  1.000000  0.050055   NaN  0.398516\n",
       "Day   -0.021916 -0.155663  0.029900  0.050055  1.000000   NaN -0.122787\n",
       "Year        NaN       NaN       NaN       NaN       NaN   NaN       NaN\n",
       "Temp   0.606500  0.273558 -0.441228  0.398516 -0.122787   NaN  1.000000"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data4.corr()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b95f5923",
   "metadata": {},
   "source": [
    "# Transformation of Data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c24b071f",
   "metadata": {},
   "source": [
    "## Creating Dummy Values for weather column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "b24f1817",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Ozone</th>\n",
       "      <th>Solar</th>\n",
       "      <th>Wind</th>\n",
       "      <th>Month</th>\n",
       "      <th>Day</th>\n",
       "      <th>Year</th>\n",
       "      <th>Temp</th>\n",
       "      <th>Weather_C</th>\n",
       "      <th>Weather_PS</th>\n",
       "      <th>Weather_S</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>41.000000</td>\n",
       "      <td>190.0</td>\n",
       "      <td>7.4</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2010</td>\n",
       "      <td>67</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>36.000000</td>\n",
       "      <td>118.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2010</td>\n",
       "      <td>72</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12.000000</td>\n",
       "      <td>149.0</td>\n",
       "      <td>12.6</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3</td>\n",
       "      <td>2010</td>\n",
       "      <td>74</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>18.000000</td>\n",
       "      <td>313.0</td>\n",
       "      <td>11.5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4</td>\n",
       "      <td>2010</td>\n",
       "      <td>62</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>41.815126</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.3</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5</td>\n",
       "      <td>2010</td>\n",
       "      <td>56</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>20.000000</td>\n",
       "      <td>223.0</td>\n",
       "      <td>11.5</td>\n",
       "      <td>9.0</td>\n",
       "      <td>30</td>\n",
       "      <td>2010</td>\n",
       "      <td>68</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>41.000000</td>\n",
       "      <td>190.0</td>\n",
       "      <td>7.4</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2010</td>\n",
       "      <td>67</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>30.000000</td>\n",
       "      <td>193.0</td>\n",
       "      <td>6.9</td>\n",
       "      <td>9.0</td>\n",
       "      <td>26</td>\n",
       "      <td>2010</td>\n",
       "      <td>70</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>41.815126</td>\n",
       "      <td>145.0</td>\n",
       "      <td>13.2</td>\n",
       "      <td>9.0</td>\n",
       "      <td>27</td>\n",
       "      <td>2010</td>\n",
       "      <td>77</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>18.000000</td>\n",
       "      <td>131.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>29</td>\n",
       "      <td>2010</td>\n",
       "      <td>76</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>157 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Ozone  Solar  Wind  Month  Day  Year  Temp  Weather_C  Weather_PS  \\\n",
       "1    41.000000  190.0   7.4    5.0    1  2010    67          0           0   \n",
       "2    36.000000  118.0   8.0    5.0    2  2010    72          1           0   \n",
       "3    12.000000  149.0  12.6    5.0    3  2010    74          0           1   \n",
       "4    18.000000  313.0  11.5    5.0    4  2010    62          0           0   \n",
       "5    41.815126    NaN  14.3    5.0    5  2010    56          0           0   \n",
       "..         ...    ...   ...    ...  ...   ...   ...        ...         ...   \n",
       "153  20.000000  223.0  11.5    9.0   30  2010    68          0           0   \n",
       "154  41.000000  190.0   7.4    5.0    1  2010    67          1           0   \n",
       "155  30.000000  193.0   6.9    9.0   26  2010    70          0           1   \n",
       "156  41.815126  145.0  13.2    9.0   27  2010    77          0           0   \n",
       "158  18.000000  131.0   8.0    9.0   29  2010    76          1           0   \n",
       "\n",
       "     Weather_S  \n",
       "1            1  \n",
       "2            0  \n",
       "3            0  \n",
       "4            1  \n",
       "5            1  \n",
       "..         ...  \n",
       "153          1  \n",
       "154          0  \n",
       "155          0  \n",
       "156          1  \n",
       "158          0  \n",
       "\n",
       "[157 rows x 10 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data5 = pd.get_dummies(data4, columns = ['Weather'])\n",
    "data5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "4cf6854a",
   "metadata": {},
   "outputs": [],
   "source": [
    "data6 = data5.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "0b5e1f81",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Ozone</th>\n",
       "      <th>Solar</th>\n",
       "      <th>Wind</th>\n",
       "      <th>Month</th>\n",
       "      <th>Day</th>\n",
       "      <th>Year</th>\n",
       "      <th>Temp</th>\n",
       "      <th>Weather_C</th>\n",
       "      <th>Weather_PS</th>\n",
       "      <th>Weather_S</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>41.000000</td>\n",
       "      <td>190.0</td>\n",
       "      <td>7.4</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2010</td>\n",
       "      <td>67</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>36.000000</td>\n",
       "      <td>118.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2010</td>\n",
       "      <td>72</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>12.000000</td>\n",
       "      <td>149.0</td>\n",
       "      <td>12.6</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3</td>\n",
       "      <td>2010</td>\n",
       "      <td>74</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>18.000000</td>\n",
       "      <td>313.0</td>\n",
       "      <td>11.5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4</td>\n",
       "      <td>2010</td>\n",
       "      <td>62</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>23.000000</td>\n",
       "      <td>299.0</td>\n",
       "      <td>8.6</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7</td>\n",
       "      <td>2010</td>\n",
       "      <td>65</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>20.000000</td>\n",
       "      <td>223.0</td>\n",
       "      <td>11.5</td>\n",
       "      <td>9.0</td>\n",
       "      <td>30</td>\n",
       "      <td>2010</td>\n",
       "      <td>68</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>41.000000</td>\n",
       "      <td>190.0</td>\n",
       "      <td>7.4</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2010</td>\n",
       "      <td>67</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>30.000000</td>\n",
       "      <td>193.0</td>\n",
       "      <td>6.9</td>\n",
       "      <td>9.0</td>\n",
       "      <td>26</td>\n",
       "      <td>2010</td>\n",
       "      <td>70</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>41.815126</td>\n",
       "      <td>145.0</td>\n",
       "      <td>13.2</td>\n",
       "      <td>9.0</td>\n",
       "      <td>27</td>\n",
       "      <td>2010</td>\n",
       "      <td>77</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>18.000000</td>\n",
       "      <td>131.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>29</td>\n",
       "      <td>2010</td>\n",
       "      <td>76</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>149 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Ozone  Solar  Wind  Month  Day  Year  Temp  Weather_C  Weather_PS  \\\n",
       "1    41.000000  190.0   7.4    5.0    1  2010    67          0           0   \n",
       "2    36.000000  118.0   8.0    5.0    2  2010    72          1           0   \n",
       "3    12.000000  149.0  12.6    5.0    3  2010    74          0           1   \n",
       "4    18.000000  313.0  11.5    5.0    4  2010    62          0           0   \n",
       "7    23.000000  299.0   8.6    5.0    7  2010    65          0           1   \n",
       "..         ...    ...   ...    ...  ...   ...   ...        ...         ...   \n",
       "153  20.000000  223.0  11.5    9.0   30  2010    68          0           0   \n",
       "154  41.000000  190.0   7.4    5.0    1  2010    67          1           0   \n",
       "155  30.000000  193.0   6.9    9.0   26  2010    70          0           1   \n",
       "156  41.815126  145.0  13.2    9.0   27  2010    77          0           0   \n",
       "158  18.000000  131.0   8.0    9.0   29  2010    76          1           0   \n",
       "\n",
       "     Weather_S  \n",
       "1            1  \n",
       "2            0  \n",
       "3            0  \n",
       "4            1  \n",
       "7            0  \n",
       "..         ...  \n",
       "153          1  \n",
       "154          0  \n",
       "155          0  \n",
       "156          1  \n",
       "158          0  \n",
       "\n",
       "[149 rows x 10 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data6"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b4bd4297",
   "metadata": {},
   "source": [
    "# Normalization of the Data range(0 to 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "e0f854bc",
   "metadata": {},
   "outputs": [],
   "source": [
    "from numpy import set_printoptions\n",
    "from sklearn.preprocessing import MinMaxScaler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "a4693f16",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 41.        , 190.        ,   7.4       , ...,   0.        ,\n",
       "          0.        ,   1.        ],\n",
       "       [ 36.        , 118.        ,   8.        , ...,   1.        ,\n",
       "          0.        ,   0.        ],\n",
       "       [ 12.        , 149.        ,  12.6       , ...,   0.        ,\n",
       "          1.        ,   0.        ],\n",
       "       ...,\n",
       "       [ 30.        , 193.        ,   6.9       , ...,   0.        ,\n",
       "          1.        ,   0.        ],\n",
       "       [ 41.81512605, 145.        ,  13.2       , ...,   0.        ,\n",
       "          0.        ,   1.        ],\n",
       "       [ 18.        , 131.        ,   8.        , ...,   1.        ,\n",
       "          0.        ,   0.        ]])"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data6.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "2198b500",
   "metadata": {},
   "outputs": [],
   "source": [
    "array = data6.values\n",
    "scaler = MinMaxScaler(feature_range=(0,1))\n",
    "rescaledX = scaler.fit_transform(array)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bef11ba1",
   "metadata": {},
   "source": [
    "### Summarize Transform data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "bef2eb4e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0.24 0.56 0.3  0.   0.   0.   0.25 0.   0.   1.  ]\n",
      " [0.21 0.34 0.33 0.   0.03 0.   0.38 1.   0.   0.  ]\n",
      " [0.07 0.43 0.57 0.   0.07 0.   0.43 0.   1.   0.  ]\n",
      " [0.1  0.94 0.52 0.   0.1  0.   0.12 0.   0.   1.  ]\n",
      " [0.13 0.89 0.36 0.   0.2  0.   0.2  0.   1.   0.  ]]\n"
     ]
    }
   ],
   "source": [
    "set_printoptions(precision = 2)\n",
    "print(rescaledX[0:5])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f268197c",
   "metadata": {},
   "source": [
    "# Standardize data (0 mean, 1 std) range(-3 sigma to +3 sigma)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "32d8116f",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import StandardScaler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "f8bf3ed5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[-0.03  0.05 -0.73 -1.46 -1.71  0.   -1.22 -0.66 -0.67  1.25]\n",
      " [-0.2  -0.77 -0.56 -1.46 -1.6   0.   -0.67  1.52 -0.67 -0.8 ]\n",
      " [-1.04 -0.42  0.76 -1.46 -1.48  0.   -0.45 -0.66  1.5  -0.8 ]\n",
      " [-0.83  1.43  0.44 -1.46 -1.37  0.   -1.77 -0.66 -0.67  1.25]\n",
      " [-0.66  1.27 -0.39 -1.46 -1.03  0.   -1.44 -0.66  1.5  -0.8 ]]\n"
     ]
    }
   ],
   "source": [
    "stdarray = data6.values\n",
    "\n",
    "stdscaler = StandardScaler().fit(stdarray)\n",
    "stdrescaledX = stdscaler.transform(stdarray)\n",
    "\n",
    "set_printoptions(precision=2)\n",
    "print(stdrescaledX[0:5])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b8e98e15",
   "metadata": {},
   "source": [
    "#  Speed Up EDA Process"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "61b06783",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas_profiling as pp\n",
    "import sweetviz as sv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "564c36d7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "be7f838da8514c9ab7dc67136ec5e092",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Summarize dataset:   0%|          | 0/5 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ff270487f2ae4b0498a4f6c9c2649404",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Generate report structure:   0%|          | 0/1 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "19c6bb15571a43aea71660026c9ffea3",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Render HTML:   0%|          | 0/1 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d150748c56374503ba2c04b501b13a09",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Export report to file:   0%|          | 0/1 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "EDA_report_pp = pp.ProfileReport(data)\n",
    "EDA_report_pp.to_file(output_file='PP_report.html')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "f3a10d94",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "81ccee0590954349a0a170f93fa7ba31",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "                                             |          | [  0%]   00:00 -> (? left)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Report Sweet_report.html was generated! NOTEBOOK/COLAB USERS: the web browser MAY not pop up, regardless, the report IS saved in your notebook/colab files.\n"
     ]
    }
   ],
   "source": [
    "sweet = sv.analyze(data)\n",
    "sweet.show_html('Sweet_report.html')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "65f02189",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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